Tokushima University / Educator and Researcher Directory --- Ren, Fuji

Personal Web Page

http://a1-www.is.tokushima-u.ac.jp/member/ren/

https://researchmap.jp/rfj0161560 (researchmap)

https://orcid.org/0000-0003-4860-9184 (ORCID)

Field of Study

○	Language Understanding and Commnication, Affective Computing, Computer Science, Intelligent robot, Social Computing

Subject of Study

○	Emotion Robort, Machine Aided Writing, Natural Language Processing and Knowledge Engineering, Sentience Computer and Sensitivity Technique, Multi-Lingual Multi-Function Multi-Media Intelligent System Project, Machine Translation and Information Retrieval (natural language processing, knowledge engineering, sentience computer, machine translation, Machine-Aided English Writing, automatic abstracting, Dialogue machine translation, information retrieval)

Book / Paper

Book:

1.	Fuji Ren and Kazuyuki Matsumoto : 言語・音声・顔表情・脳波を総合利用した感情測定システム, CMC Publishing Co.,Ltd., Aug. 2019. (Keyword) multi modal sensing / emotion measurement system / voice / language
2.	Xiaohua Wang, Muzi Peng, Lijuan Pan, Min Hu, Chunhua Jin and Fuji Ren : Two-Level Attention with Multi-task Learning for Facial Emotion Estimation, Springer-Verlag, Dec. 2018. (Summary) Valence-Arousal model can represent complex human emotions, including slight changes of emotion. Most prior works of facial emotion estimation only considered laboratory data and used video, speech or other multi-modal features. The effect of these methods applied on static images in the real world is unknown. In this paper, a two-level attention with multi-task learning (MTL) framework is proposed for facial emotion estimation on static images. The features of corresponding region were automatically extracted and enhanced by first-level attention mechanism. And then we designed a practical structure to process the features extracted by first-level attention. In the following, we utilized Bi-directional Recurrent Neural Network (Bi-RNN) with self-attention (second-level attention) to make full use of the relationship of these features adaptively. It can be concluded as a combination of global and local information. In addition, we exploited MTL to estimate the value of valence and arousal simultaneously, which employed the correlation of the two tasks. The quantitative results conducted on AffectNet dataset demonstrated the superiority of the proposed framework. In addition, extensive experiments were carried out to analysis effectiveness of different components. (Keyword) Facial emotion estimation / Attention mechanism / Multi-task learning (Link to Publication Site) ● Publication site (DOI): 10.1007/978-3-030-05710-7_19 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1007/978-3-030-05710-7_19 (DOI: 10.1007/978-3-030-05710-7_19)
3.	Yu Gu, Tao Liu, Jie Li, Fuji Ren, Zhi Liu, Xiaoyan Wang and Peng Li : EmoSense: Data-driven Emotion Sensing via Off-the-shelf WiFi Devices, IEEE, Kansas City, USA, May 2018. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICC.2018.8422330 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85051421577 (DOI: 10.1109/ICC.2018.8422330, Elsevier: Scopus)
4.	Yu Gu, Min Peng, Fuji Ren and Jie Li : Smart Technologies for Emergency Response and Disaster Management (Chaoter 3, WiFi Fingerprint Localization for Emergency Response: Harvesting Environmental Dynamics for a Rapid Setup), IGI Global, Jan. 2018. (Link to Publication Site) ● Publication site (DOI): 10.4018/978-1-5225-2575-2.ch003 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.4018/978-1-5225-2575-2.ch003 (DOI: 10.4018/978-1-5225-2575-2.ch003)
5.	Fuji Ren, Shun Nishide, Kazuyuki Matsumoto, XIN KANG, Duo Feng and Mengjia He : Artificial Intelligence with Uncertainty, NTS, Jun. 2017.
6.	Fuji Ren and Kazuyuki Matsumoto : Natural Language Processing Capabilities Required for Humanoid Nursing Robots, Fukuro Shuppan Publishing, Mar. 2017.
7.	Kazuyuki Matsumoto, Fuji Ren, Minoru Yoshida and Kenji Kita : Refinement by Filtering Translation Candidates and Similarity Based Approach to Expand Emotion Tagged Corpus, Jan. 2017. (Summary) We attempted to expand corpus without translating target linguistic resource. The result of the evaluation experiment using the machine learning algorithm showed the effectiveness of the expanded emotion corpus based on the original languages unannotated sentences and their similar sentences. (Keyword) emotion tagged corpus / Japanese-English parallel corpora / emotion estimation (Link to Publication Site) ● Publication site (DOI): 10.1007/978-3-319-52758-1_15 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85011342735 (DOI: 10.1007/978-3-319-52758-1_15, Elsevier: Scopus)
8.	Zhongzhi Shi, Ben Goertzel and Fuji Ren : Advanced Intelligence, Tsinghua University Press,, Beijing, Aug. 2010.
9.	Fuji Ren : Language Engineering, Affective Computing and Advanced Intelligence, BUPT publishing House, Dec. 2009.
10.	Ye Wu and Fuji Ren : A Corpus-based Multi-label Emotion Classification using Maximum Entropy, --- 20. Natural Language Processing and Cognitive Science, B. Sharp. and M. Zock (Eds.) ---, INSTICC Press, Jun. 2009.
11.	Fuji Ren : Advanced Intelligence, International Advanced Information Institute, Dec. 2008.
12.	Fuji Ren, Yixin Zhong, Shingo Kuroiwa and Satoru Tsuge : Artificial Intelligence and Affective Computing, International Advanced Information Institute, Jun. 2007.
13.	Fuji Ren : Artificial Intelligence, 中国科学出版社, Beijing, Jun. 2006.
14.	Fuji Ren and J.L. Feng : 科学技術前縁, 中国科学技術出版社, Beijing, May 2003. (Summary) 現代科学技術発展の特徴の一つとしては，科学発見と技術発明から産業応用までのスピードが益々速く，周期も益々短くなる．この本では科学技術の前縁的な課題，成果，進展と動向を紹介する．内容は以下のようなメイン課題である．情報処理の方法·動向，画像処理と植物生産への応用，現代ロボット，インターフェース，複雑システム，通信技術，材料とエネルギー，生物医療，遺伝工学などがある．
15.	中野靖久, Fuji Ren and 寺内衛 : 教養としての情報処理, 株式会社大学教育出版, Apr. 2001. (Summary) 情報処理の基礎，一般情報処理演習の教材として，コンピュータの仕組み，ワークステーションの基本的な使い方，ウィンドウズの基本操作，文章の作成，図表の作成の方法，及び電子メールなどの使い方を述べる．
16.	Li Lei and Fuji Ren : Information, International Information Institute Press, Oct. 2000. (Summary) 国際会議Information-2000で発表された論文から精選された論文集である．自然科学と数学，工学と農学，医療と人工生命，経済と社会に渡る広範囲の情報について最新の進展と成果を述べる．さらに，諸分野での今後の課題と展望について述べる．
17.	Zhang Jianping and Fuji Ren : Geography Information System and MapInfo, Science Press, May 1999. (Summary) 本書では地理情報システム(GIS)の基本知識及びMapInfoの応用技術を述べる．以下の3部分で構成される．第1部分は地理情報システム及びその開発技術を記述する．第2部分は地理情報システムの基本ソフトの使用方法及び応用実例を述べる．第3部分はMapBasic言語及びその応用について述べる．
18.	Fan Lixin, Fuji Ren, Miyanaga Yoshikazu and Tochinai Koji : Automatic Composition of Chinese Compound Words for Chinese-Japanese Machine Translation System, Computational Linguistics, Nov. 1993. (Summary) 機械翻訳において文の解析を高精度で，かつ効率良く行うという観点から，できるだけ複合語単位で処理することが望ましく，個別の単語として扱うと，構文解析結果に曖昧性を発生しやすく，以後の翻訳過程に大きな影響を与える．本論文では，中日機械翻訳のための中国語文の複合語の自動合成手法を提案する．本手法の特徴として，(1)形態素解析の誤りを避けるため，動詞性の兼用品詞からなる複合語は辞書に登録せず，その都度合成すること，(2)構文解析の曖昧性を減少または解消するため，できるだけ早い段階で複合語を合成すること，(3)複合語合成ルールを用意して複合語合成を容易に実現し，処理時間を短縮すること，などがあげられる．この手法に基づく実験システムを構築し，実験により，本論文で提案した手法の有効性を確認された．
19.	Fuji Ren : On Reservable Structural Ambiguities in Logically Parallel Translation System, Computational Linguistics, Nov. 1993. (Summary) 本論文では，超並列機械翻訳というパラダイムを提案する．超並列機械翻訳とは，超並列計算機という新しい計算機アーキテクチャ及び超並列モデルを基盤として，超並列人工知能技術を利用する機械翻訳に関する研究である．我々は超並列機械翻訳を，物理的張並列機械翻訳と論理的張並列機械翻訳に大別する．本論文では論理的超並列機械翻訳の概念と手法を述べ，日中機械翻訳を例としてシステムの構成概要を紹介する．論理的超並列機械翻訳は多数のモジュールから構成される．その中に翻訳の流れ，翻訳の動作を制御するモジュールがある．これを制御モジュールという．その他のモジュールが並列に各自の仕事をする．制御モジュールの機能は，入力した原言語文を多数独立のタスクに分けて，これを相応のモジュールに提供する．そして，各モジュールから提供した結果を総合して最終の訳文を生成する．このような概念に基づき，日中機械翻訳を構築するための家族モデルを開発した．このシステムでは，現在5つの独立のモジュールを持っている．最後に文章の並列性の抽出，問題別のアルゴリズムの開発などを述べる．
20.	Fuji Ren and 范莉馨 : 基於家族模型的機器翻訳系統, 科学技術出版社, Beijing, May 1992. (Summary) 我々は機械翻訳の新しい方法とする家族モデルを提案したが，このモデルを用い日中機械翻訳を開発し，その手法の有効性を評価する実験を行った．本論文ではこの実験結果を報告し，並列的な機械翻訳概念を提案した．
21.	Fan Lixin, Fuji Ren, 宮永喜一 and 栃内香次 : 利用句構造特徴実現的機械翻訳, 科学技術出版社, Beijing, May 1992. (Summary) 文を構成する句の特徴などを検討し，いろいろな句の構文特徴と意味関連性を抽出した．本論文ではこのような句の特徴に着目し，自動翻訳ルールを纏めた．さらに，このような翻訳ルールを開発している機械翻訳システムに組み込んで実験を行った．

Academic Paper (Judged Full Paper):

1.	Shi Xuefeng, Yang Ming, Hu Min, Fuji Ren, XIN KANG and Ding Weiping : Affective knowledge assisted bi-directional learning for Multi-modal Aspect-based Sentiment Analysis, Computer Speech & Language, Vol.91, 1-16, 2025.
2.	Linhuang Wang, XIN KANG, Fei Ding, Satoshi Nakagawa and Fuji Ren : A Joint Local Spatial and Global Temporal CNN-Transformer for Dynamic Facial Expression Recognition, Applied Soft Computing, Vol.161, 1-13, 2024. (Keyword) Dynamic facial expression recognition / Affective computing / Transformer / Convolution neural network (Tokushima University Institutional Repository) ● Metadata: 119348 (Link to Publication Site) ● Publication site (DOI): 10.1016/j.asoc.2024.111680 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1016/j.asoc.2024.111680 (Tokushima University Institutional Repository: 119348, DOI: 10.1016/j.asoc.2024.111680)
3.	Fei Ding, XIN KANG, Linhuang Wang, Yunong Wu, Satoshi Nakagawa and Fuji Ren : Causal Inference and Prefix Prompt Engineering Based on Text Generation Models for Financial Argument Analysis, Electronics, Vol.13, No.9, 1-16, 2024. (Keyword) Generative Learning / Financial Argument Analysis / Prompt Engineering / causal inference (Tokushima University Institutional Repository) ● Metadata: 119666 (Link to Publication Site) ● Publication site (DOI): 10.3390/electronics13091746 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.3390/electronics13091746 (Tokushima University Institutional Repository: 119666, DOI: 10.3390/electronics13091746)
4.	Fei Ding, XIN KANG and Fuji Ren : Neuro or Symbolic? Fine-tuned Transformer with Unsupervised LDA Topic Clustering for Text Sentiment Analysis, IEEE Transactions on Affective Computing, Vol.15, No.2, 493-507, 2024. (Tokushima University Institutional Repository) ● Metadata: 118516 (Link to Publication Site) ● Publication site (DOI): 10.1109/TAFFC.2023.3279318 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/TAFFC.2023.3279318 (Tokushima University Institutional Repository: 118516, DOI: 10.1109/TAFFC.2023.3279318)
5.	Fuji Ren, Yangyang Zhou, Jiawen Deng, Kazuyuki Matsumoto, Duo Feng, Tianhao She, Ziyun Jiao, Zheng Liu, Taihao Li, Satoshi Nakagawa and XIN KANG : Tracking Emotions using an Evolutionary Model of Mental State Transitions: Introducing a New Paradigm, Intelligent Computing, 1-24, 2024. (Tokushima University Institutional Repository) ● Metadata: 119667 (Link to Publication Site) ● Publication site (DOI): 10.34133/icomputing.0075 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.34133/icomputing.0075 (Tokushima University Institutional Repository: 119667, DOI: 10.34133/icomputing.0075)
6.	Yuxiang Zhou, XIN KANG, Fuji Ren, Huimin Lu, Satoshi Nakagawa and Xiao Shan : A Multi-attention and Depthwise Separable Convolution Network for Medical Image Segmentation, Neurocomputing, Vol.15, No.1, 121-129, 2024. (Keyword) U-Net / dual attention / attention gate / depthwise separable convolution / medical image segmentation (Tokushima University Institutional Repository) ● Metadata: 118693 (Link to Publication Site) ● Publication site (DOI): 10.1016/j.neucom.2023.126970 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1016/j.neucom.2023.126970 (Tokushima University Institutional Repository: 118693, DOI: 10.1016/j.neucom.2023.126970)
7.	LIU ZHENG, XIN KANG and Fuji Ren : Dual-TBNet: Improving the Robustness of Speech Features via Dual-Transformer-BiLSTM for Speech Emotion Recognition, IEEE/ACM Transactions on Audio, Speech, and Language Processing, Vol.31, 2193-2203, 2023. (Keyword) speech emotion recognition / affective computing / speech representation learning / feature fusion Transformer (Tokushima University Institutional Repository) ● Metadata: 118515 (Link to Publication Site) ● Publication site (DOI): 10.1109/TASLP.2023.3282092 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/TASLP.2023.3282092 (Tokushima University Institutional Repository: 118515, DOI: 10.1109/TASLP.2023.3282092)
8.	Yangyang Zhou, XIN KANG and Fuji Ren : Prompt Consistency for Multi-label Textual Emotion Detection, IEEE Transactions on Affective Computing, 1-10, 2023. (Tokushima University Institutional Repository) ● Metadata: 118259 (Link to Publication Site) ● Publication site (DOI): 10.1109/TAFFC.2023.3254883 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85149879267 (Tokushima University Institutional Repository: 118259, DOI: 10.1109/TAFFC.2023.3254883, Elsevier: Scopus)
9.	XIN KANG, Shi Xuefeng, Yunong Wu and Fuji Ren : Active learning with complementary sampling for instructing class-biased multi-label text emotion classification, IEEE Transactions on Affective Computing, Vol.14, No.1, 523-536, 2023. (Keyword) Active Learning / Complementary Sampling / Class Biased Multi Label Classification / Text Emotion (Tokushima University Institutional Repository) ● Metadata: 118256 (Link to Publication Site) ● Publication site (DOI): 10.1109/TAFFC.2020.3038401 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/TAFFC.2020.3038401 (Tokushima University Institutional Repository: 118256, DOI: 10.1109/TAFFC.2020.3038401)
10.	Fuji Ren, Zheng Liu and XIN KANG : An efficient framework for constructing speech emotion corpus based on integrated active learning strategies, IEEE Transactions on Affective Computing, Vol.13, No.4, 1929-1940, 2022. (Tokushima University Institutional Repository) ● Metadata: 118257 (Link to Publication Site) ● Publication site (DOI): 10.1109/TAFFC.2022.3192899 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/TAFFC.2022.3192899 (Tokushima University Institutional Repository: 118257, DOI: 10.1109/TAFFC.2022.3192899)
11.	Li Zhiyang, Li Bin, Ni Hongjun, Fuji Ren, Lv Shuaishuai and XIN KANG : An Effective Surface Defect Classification Method Based on RepVGG with CBAM Attention Mechanism (RepVGG-CBAM) for Aluminum Profiles, Metals, Vol.12, No.11, 1-16, 2022. (Tokushima University Institutional Repository) ● Metadata: 118180 (Link to Publication Site) ● Publication site (DOI): 10.3390/met12111809 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85141827896 (Tokushima University Institutional Repository: 118180, DOI: 10.3390/met12111809, Elsevier: Scopus)
12.	Kazuyuki Matsumoto, Manabu Sasayama, Minoru Yoshida, Kenji Kita and Fuji Ren : Emotion Analysis and Dialogue Breakdown Detection in Dialogue of Chat Systems Based on Deep Neural Networks, Electronics, Vol.11, No.5, 2022. (Summary) In dialogues between robots or computers and humans, dialogue breakdown analysis is an important tool for achieving better chat dialogues. Conventional dialogue breakdown detection methods focus on semantic variance. Although these methods can detect dialogue breakdowns based on semantic gaps, they cannot always detect emotional breakdowns in dialogues. In chat dialogue systems, emotions are sometimes included in the utterances of the system when responding to the speaker. In this study, we detect emotions from utterances, analyze emotional changes, and use them as the dialogue breakdown feature. The proposed method estimates emotions by utterance unit and generates features by calculating the similarity of the emotions of the utterance and the emotions that have appeared in prior utterances. We employ deep neural networks using sentence distributed representation vectors as the feature. In an evaluation of experimental results, the proposed method achieved a higher dialogue breakdown detection rate when compared to the method using a sentence distributed representation vectors. (Keyword) natural language processing / dialogue breakdown / human-computer dialogue system / sentiment analysis / emotion recognition (Tokushima University Institutional Repository) ● Metadata: 116757 (Link to Publication Site) ● Publication site (DOI): 10.3390/electronics11050695 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.3390/electronics11050695 (Tokushima University Institutional Repository: 116757, DOI: 10.3390/electronics11050695)
13.	Qian Zhang and Fuji Ren : Double bayesian pairwise learning for one-class collaborative filtering, Knowledge-based Systems, Vol.440, 2-13, 2021. (Summary) Recommender systems have become an indispensable tool for real-world applications. Only one-class feedback can be obtained in many applications. Therefore, the one-class recommendation problem has attracted much attention. Pairwise ranking methods are popular for dealing with the one-class problem. Bayesian Personalized Ranking (BPR) is one of the most popular pairwise methods, assuming users prefer the observed item to the unobserved item. The parameters in BPR are learned based on stochastic gradient descent (SGD). However, the previous work has shown that existing the vanishing gradient problem in the learning process when the preference difference between the observed item and the unobserved item is very large. In this paper, we propose a novel algorithm called Double Bayesian Pairwise Learning (DBPL). In the learning process of DBPL, the preference difference between the observed item and the unobserved item can be reduced by fusing a relatively smaller preference difference between another pair of items. Moreover, we calculate potential preference scores between users and items based on user-item interactions to measure preference differences between unobserved items of each user. Experimental results on three real-world datasets show the effectiveness of the DBPL algorithm. (Link to Publication Site) ● Publication site (DOI): 10.1016/j.knosys.2021.107339 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1016/j.knosys.2021.107339 (DOI: 10.1016/j.knosys.2021.107339)
14.	Siyuan Xue and Fuji Ren : Intent-Enhanced Attentive Bert Capsule Network for Zero-shot Intention Detection, Neurocomputing, 2-15, 2021. (Summary) Spoken language understanding (SLU) plays an indispensable role in the dialogue system. The traditional intention detection task is regarded as a classification problem where utterances are associated with pre-defined intents. However, the various expressions of user's intents and constantly emerging novel intents make the annotating time-consuming and labor-intensive, building massive obstacles for extending the model to new tasks. Identifying unexpected user intention and achieving the user's desire goal is a challenging task. Therefore, we conduct zero-shot intention detection based on a transformation-based learning manner. In this paper, we propose an intent-enhanced attentive capsule network (IE-BertCapsNet) further guides the aggregation process of the capsule network and generalizable useful features that can be adapted to emerging intentions. Coupling with the large margin cosine loss function, the proposed model can identify discriminative features by forcing the whole network to minimize inter-class distance and minimize intra-class distance. Finally, we leverage the IE-BertCapsNet's feature extraction ability and knowledge transferring capability to conduct zero-shot intent detection and generalized zero-shot intent detection. Extensive experiments on five benchmark task-oriented datasets in four languages demonstrate that the proposed model can achieve competitive performance that can better discriminate known intents and detect unknown intents. (Link to Publication Site) ● Publication site (DOI): 10.1016/j.neucom.2021.05.085 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1016/j.neucom.2021.05.085 (DOI: 10.1016/j.neucom.2021.05.085)
15.	Min Hu, Qian Chu, Xiaohua Wang, Lei He and Fuji Ren : A Two-Stage Spatiotemporal Attention Convolution Network for Continuous Dimensional Emotion Recognition from Facial Video, IEEE Signal Processing Letters, 1-20, 2021. (Summary) Continuous dimensional emotion recognition for facial video sequence is a crucial and challenging task in Affective Computing and Human-Computer Intelligent Interaction. The key of this task is to effectively extract and discriminate spatialtemporal features in a more fine-grained way. In this paper, a Two-Stage Spatiotemporal Attention Temporal Convolution Network (TS-SATCN) is designed for continuous dimensional emotion recognition of facial videos. The first stage generates an initial recognition result that is later fed into the second for correction. In each stage, the introduced spatiotemporal attention branch helps the network learn different attention levels and focuses on the informative spatial-temporal features adaptively. The network is trained by a proposed smooth loss function which can further improve the predictions quality. Extensive experiments are performed on two datasets, RECOLA and AFEW-VA, which shows that the proposed method achieves significant improvement over state-of-the-art methods. (Link to Publication Site) ● Publication site (DOI): 10.1109/LSP.2021.3063609 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/LSP.2021.3063609 (DOI: 10.1109/LSP.2021.3063609)
16.	Yu Gu, Huan Yan, Mianxiong Dong, Meng Wang, Xiang Zhang, Zhi Liu and Fuji Ren : WiONE: One-Shot Learning for Environment-Robust Device-Free User Authentication via Commodity Wi-Fi in Man-Machine System, IEEE Transactions on Computational Social Systems, 1-13, 2021. (Summary) User authentication is the first and most critical step in protecting a man-machine system from a malicious spoofer. However, security and privacy are just like the two sides of one coin, hard to see both at the same time, especially by the current mainstream credential- and biometric-based approaches. To this end, we propose WiONE, a safe and privacy-preserving user authentication system leveraging the ubiquitous Wi-Fi infrastructure by exploring ``how you behave'' rather than ``who you are''. The key idea is to apply deep learning to user physical behavior captured by Wi-Fi channel state information (CSI) to identify legitimate users while rejecting spoofers. The design of WiONE faces two challenges, namely, how to capture the subtle behavior, such as a keystroke on CSI, and how to mitigate the heavy environment-specific training required by deep learning. For the former, we design a behavior enhancement model based on the Rician fading to highlight the behavior-induced information by suppressing the behavior-unrelated information on channel response. For the latter, we develop a behavior characterization method tailored for the prototypical networks to facilitate the extraction of the domain-independent behavioral features and enable one-shot recognition of a new user in a new environment. Numerous experiments are conducted in several real-world environments, and the results show that WiONE outperforms its state-of-the-art rivals in authentication performance with much less training effort. (Link to Publication Site) ● Publication site (DOI): 10.1109/TCSS.2021.3056654 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85103265541 (DOI: 10.1109/TCSS.2021.3056654, Elsevier: Scopus)
17.	Min Hu, Fei Qian, Xiaohua Wang, Lei He, Dong Guo and Fuji Ren : Robust Heart Rate Estimation with Spatial-Temporal Attention Network from Facial Videos, IEEE Transactions on Cognitive and Developmental Systems, 1-20, 2021. (Summary) In order to solve the problems of highly redundant spatial information and motion noise in the heart rate (HR) estimation from facial videos based on remote Photoplethysmography(rPPG), this paper proposes a novel HR estimation method based on spatial-temporal attention model. Firstly, to reduce the redundant information and strengthen the association relationships of long-range videos, the spatial-temporal facial features are extracted by the 2D convolutional neural network (2DCNN) and 3D convolutional neural network (3DCNN), respectively. The aggregation function is adopted to incorporate feature maps into short segment spatial-temporal feature maps. Secondly, the spatial-temporal strip pooling is designed in the spatial-temporal attention module to reduce head movement noises. Then, via the two-part loss function, the model can focus more on the rPPG signal rather than the interference. We conduct extensive experiments on two public datasets to verify the effectiveness of our model. The experimental results show that the proposed method achieves significantly better performances than the state-of-the-art baselines: The mean absolute error could be reduced by 11% on the PURE dataset, and by 25% on the COHFACE dataset. (Link to Publication Site) ● Publication site (DOI): 10.1109/TCDS.2021.3062370 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/TCDS.2021.3062370 (DOI: 10.1109/TCDS.2021.3062370)
18.	Qian Zhang and Fuji Ren : Prior-based bayesian pairwise ranking for one-class collaborative filtering, Neurocomputing, Vol.440, 365-374, 2021. (Summary) In many real-world applications, only user-item interactions (one-class feedback) can be observed. The recommendation methods have been studied for personalized ranking with one-class feedback in recent years. Pairwise ranking methods have been widely used for dealing with the one-class problem with the assumption that users prefer their observed items over unobserved items. However, existing some items that users have not seen yet. It is unsuitable for treating all unobserved items of the user as negative feedback. In this paper, we propose a Prior-based Bayesian Pairwise Ranking (PBPR) model, which relaxes the simple pairwise preference assumption in previous works by further considering the pairwise preference between two unobserved items. Moreover, we calculate users' potential preference scores on unobserved items, i.e., prior information, based on historical interactions. The prior information can be used to measure the fine-grained preference difference between any two unobserved items of each user. Through extensive experiments on real-world datasets, we demonstrate the effectiveness of our proposed recommendation method. (Tokushima University Institutional Repository) ● Metadata: 116029 (Link to Publication Site) ● Publication site (DOI): 10.1016/j.neucom.2021.01.117 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1016/j.neucom.2021.01.117 (Tokushima University Institutional Repository: 116029, DOI: 10.1016/j.neucom.2021.01.117)
19.	Jiawen Deng and Fuji Ren : A Survey of Textual Emotion Recognition and Its Challenges, IEEE Transactions on Affective Computing, 1-20, 2021. (Summary) Textual language is the most natural carrier of human emotion. In natural language processing, textual emotion recognition (TER) has become an important topic due to its significant academic and commercial potential. With the advanced development of deep learning technologies, TER has attracted growing attention and has significantly been promoted in recent years. This paper provides a systematic survey of latest TER advances, focusing on approaches using deep neural networks. According to how deep learning works at each stage, TER approaches are reviewed on word embedding, architecture, and training levels, respectively. We discussed the remaining challenges and opportunities from four aspects: the shortage of large-scale and high-quality dataset, fuzzy emotional boundaries, incomplete extractable emotional information in texts, and TER in dialogue. This paper creates a systematic and in-depth overview of deep TER technologies. It provides the necessary knowledge and new insights for relevant researchers to understand better the research state, remaining challenges, and future directions in this field. (Link to Publication Site) ● Publication site (DOI): 10.1109/TAFFC.2021.3053275 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/TAFFC.2021.3053275 (DOI: 10.1109/TAFFC.2021.3053275)
20.	Haitao Yu, Degen Huang, Fuji Ren and Lishuang Li : Diagnostic Evaluation of Policy-Gradient-Based Ranking, Electronics, Vol.10, No.19, 1-21, 2021. (Summary) Learning-to-rank has been intensively studied and has shown significantly increasing values in a wide range of domains, such as web search, recommender systems, dialogue systems, machine translation, and even computational biology, to name a few. In light of recent advances in neural networks, there has been a strong and continuing interest in exploring how to deploy popular techniques, such as reinforcement learning and adversarial learning, to solve ranking problems. However, armed with the aforesaid popular techniques, most studies tend to show how effective a new method is. A comprehensive comparison between techniques and an in-depth analysis of their deficiencies are somehow overlooked. This paper is motivated by the observation that recent ranking methods based on either reinforcement learning or adversarial learning boil down to policy-gradient-based optimization. Based on the widely used benchmark collections with complete information (where relevance labels are known for all items), such as MSLRWEB30K and Yahoo-Set1, we thoroughly investigate the extent to which policy-gradient-based ranking methods are effective. On one hand, we analytically identify the pitfalls of policy-gradient-based ranking. On the other hand, we experimentally compare a wide range of representative methods. The experimental results echo our analysis and show that policy-gradient-based ranking methods are, by a large margin, inferior to many conventional ranking methods. Regardless of whether we use reinforcement learning or adversarial learning, the failures are largely attributable to the gradient estimation based on sampled rankings, which significantly diverge from ideal rankings. In particular, the larger the number of documents per query and the more fine-grained the ground-truth labels, the greater the impact policy-gradient-based ranking suffers. Careful examination of this weakness is highly recommended for developing enhanced methods based on policy gradient. (Tokushima University Institutional Repository) ● Metadata: 117218 (Link to Publication Site) ● Publication site (DOI): 10.3390/electronics11010037 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.3390/electronics11010037 (Tokushima University Institutional Repository: 117218, DOI: 10.3390/electronics11010037)
21.	Min Hu, Dong Guo, Mingxing Jiang, Fei Qian, Xiaohua Wang and Fuji Ren : rPPG-Based Heart Rate Estimation using Spatial-Temporal Attention Network, IEEE Transactions on Cognitive and Developmental Systems, 1-20, 2021. (Summary) Remote photoplethysmography (rPPG) based on computer vision technology is widely used to calculate the heart rate (HR) from facial videos. Existing rPPG techniques have been subject to some limitations (e.g., highly redundant spatial information, head movement noise and region of interest (ROI) selection). To address these limitations, this paper introduces an effective spatial-temporal attention network. A temporal fusion module is firstly proposed to fully exploit the time-domain information, aiming to reduce the redundant video information and strengthen the association relationships of long-range videos. Furthermore, a spatial attention mechanism is designed in the backbone net to precisely target the skin ROIs. Finally, to assist the network in learning the weights between channels, we project the RGB images using plane orthogonal to skin (POS) algorithm and add motion representation to complement physiological signals' extraction. Extensive experiments on the public PURE, MMSE-HR, and UBFC-rPPG datasets demonstrate that our model achieve competitive results compared with other methods. (Link to Publication Site) ● Publication site (DOI): 10.1109/TCDS.2021.3131197 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/TCDS.2021.3131197 (DOI: 10.1109/TCDS.2021.3131197)
22.	Mingxing Jiang, Liquan Shen, Min Hu, Ping An and Fuji Ren : Blind Quality Evaluator of Tone-Mapped HDR and Multi-Exposure Fused Images for Electronic Display, IEEE Transactions on Consumer Electronics, 1-13, 2021. (Summary) The problem of reproducing high dynamic range (HDR) images on electronic display and photography with restricted dynamic range has gained a lot of interest in the consumer electronics community. There exist various approaches to this issue, e.g., tone mapping operators (TMOs) and multi-exposure fusion algorithms (MEFs). Many existing image quality assessment (IQA) methods have been proposed to compare images of quality degradation generated by TMOs/MEFs. Although promising performances have been achieved, they seldom consider local specific artifacts difference (i.e., abnormal exposure and color cast) related with the TMOs/MEFs. To address this limitation, this paper proposes a Blind Quality Evaluator of Tone-Mapped HDR and Multi-Exposure Fused Images (BQE-TM/MEFI). First, two purpose-designed segment models are utilized to distinguish well-exposedness dense patches (WEDPes) and non-WEDPes, color cast patches (CCPes) and non-CCPes respectively. Second, multiple quality-perception features are extracted to measure local artifacts: 1) structure and sharpness features from WEDPes, 2) saturation features from non-CCPes, and 3) edge structure features. Then, three new low-complexity regional features (over-exposure ratio, entropy and color confidence index) are calculated based on over-exposure segmentation model. Finally, all extracted features are aggregated into a machine-learning regression model to pool a quality score. The simplicity and good performance of the proposed method makes it suitable for electronic displays and other consumer electronics. (Link to Publication Site) ● Publication site (DOI): 10.1109/TCE.2021.3130176 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/TCE.2021.3130176 (DOI: 10.1109/TCE.2021.3130176)
23.	Yu Gu, Huan Yan, Xiang Zhang, Zhi Liu and Fuji Ren : 3D Facial Expression Recognition via Attention-based Multi-channel Data Fusion Network, IEEE Transactions on Instrumentation and Measurement, 1-11, 2021. (Summary) Facial expression has long been recognized as containing meaningful non-verbal affective cues for decoding human emotions. Recently, multi-modal 2D+3D fusion method has shown significant potential in facial expression recognition (FER) due to its fine-grained face descriptions in various spatial channels. However, current work mainly relies on feature-level or even score-level fusion to find emotion cues spread in different channels, and may miss key information due to lack of focus. To this end, we propose an attention-based multi-channel data fusion network (AMDFN) to better preserve and find such key facial cues. More specifically, we first map a 3D face scan into multi-channel images, and then fuse them in a ResNet18 backbone to get layered emotion features. Secondly, we leverage a layer attention model to explore the dependencies between features of different layers to learn discriminative affective cues for effective emotion recognition. Our comprehensive experiments on two widely-used datasets (i.e., Facescape and Bosphorus) have verified the performance of our approach compared to several state-of-the-art rivals. (Link to Publication Site) ● Publication site (DOI): 10.1109/TIM.2021.3125972 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/TIM.2021.3125972 (DOI: 10.1109/TIM.2021.3125972)
24.	Fuji Ren and Tianhao She : Utilizing External Knowledge to Enhance Semantics in Emotion Detection in Conversation, IEEE Access, Vol.10, No.19, 1-11, 2021. (Summary) Enabling machines to emotion recognition in conversation is challenging, mainly because information in human dialogue innately conveys emotions by long-term experience, abundant knowledge, context, and the intricate patterns between the affective states. We address the task of emotion recognition in conversations using external knowledge to enhance semantics. We propose KES model, a new framework that incorporates different elements of external knowledge and conversational semantic role labeling, where build upon them to learn interactions between interlocutors participating in a conversation. We design a self-attention layer specialized for enhanced semantic text features with external commonsense knowledge. Then, two different networks composed of LSTM are responsible for tracking individual internal state and context external state. In addition, the proposed model has experimented on three datasets in emotion detection in conversation. The experimental results show that our model outperforms the state-of-the-art approaches on most of the tested datasets. (Tokushima University Institutional Repository) ● Metadata: 116566 (Link to Publication Site) ● Publication site (DOI): 10.1109/ACCESS.2021.3128277 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/ACCESS.2021.3128277 (Tokushima University Institutional Repository: 116566, DOI: 10.1109/ACCESS.2021.3128277)
25.	Quan Wang, Fei Wang, Fuji Ren, Zhongheng Li and Feiping Nie : An Effective Clustering Optimization Method for Unsupervised Linear Discriminant Analysis, IEEE Transactions on Knowledge and Data Engineering, 1-13, 2021. (Summary) The recent work Unsupervised Linear Discriminant Analysis (Un-LDA) completes its clustering process during the alternating optimization by converting equivalently the objective and finally using the K-means algorithm. However, the K-means algorithm has its inherent drawbacks. It is hard for the K-means algorithm to deal well with some complex clustering cases where there are too many real clusters or non-convex clusters. In this paper, a novel clustering optimization method is presented to accomplish the clustering process in Un-LDA and the resulting method can be named Un-LDA(CD). Specifically, instead of the K-means algorithm, an elaborately designed coordinate descent algorithm is adopted to obtain the clusters after the objective function goes through a series of simple but deft equivalent conversions. Extensive experiments have demonstrated that the coordinate descent clustering solution for Un-LDA can outperform the original K-means based solution on the tested data sets especially those complex data sets with a pretty large number of real clusters. (Link to Publication Site) ● Publication site (DOI): 10.1109/TKDE.2021.3124023 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/TKDE.2021.3124023 (DOI: 10.1109/TKDE.2021.3124023)
26.	Tianhao She and Fuji Ren : Enhance the Language Ability of Humanoid Robot NAO through Deep Learning to Interact with Autistic Children, Electronics, Vol.10, No.19, 1-21, 2021. (Summary) Autism spectrum disorder (ASD) is a life-long neurological disability, and a cure has not yet been found. ASD begins early in childhood and lasts throughout a person's life. Through early intervention, many actions can be taken to improve the quality of life of children. Robots are one of the best choices for accompanying children with autism. However, for most robots, the dialogue system uses traditional techniques to produce responses. Robots cannot produce meaningful answers when the conversations have not been recorded in a database. The main contribution of our work is the incorporation of a conversation model into an actual robot system for supporting children with autism. We present the use a neural network model as the generative conversational agent, which aimed at generating meaningful and coherent dialogue responses given the dialogue history. The proposed model shares an embedding layer between the encoding and decoding processes through adoption. The model is different from the canonical Seq2Seq model in which the encoder output is used only to set-up the initial state of the decoder to avoid favoring short and unconditional responses with high prior probability. In order to improve the sensitivity to context, we changed the input method of the model to better adapt to the utterances of children with autism. We adopted transfer learning to make the proposed model learn the characteristics of dialogue with autistic children and to solve the problem of the insufficient corpus of dialogue. Experiments showed that the proposed method was superior to the canonical Seq2sSeq model and the GAN-based dialogue model in both automatic evaluation indicators and human evaluation, including pushing the BLEU precision to 0.23, the greedy matching score to 0.69, the embedding average score to 0.82, the vector extrema score to 0.55, the skip-thought score to 0.65, the KL divergence score to 5.73, and the EMD score to 12.21. (Tokushima University Institutional Repository) ● Metadata: 116389 (Link to Publication Site) ● Publication site (DOI): 10.3390/electronics10192393 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.3390/electronics10192393 (Tokushima University Institutional Repository: 116389, DOI: 10.3390/electronics10192393)
27.	Wenjie Liu, Guoqing Wu and Fuji Ren : Deep Multibranch Fusion Residual Network for Insect Pest Recognition, IEEE Transactions on Cognitive and Developmental Systems, Vol.13, No.3, 705-716, 2021. (Summary) Earlier insect pest recognition is one of the critical factors for agricultural yield. Thus, an effective method to recognize the category of insect pests has become significant issues in the agricultural field. In this article, we proposed a new residual block to learn multiscale representation. In each block, it contains three branches: one is parameter-free, and the others contain several successive convolution layers. Moreover, we proposed a module and embedded it into the new residual block to recalibrate the channelwise feature response and to model the relationship of the three branches. By stacking this kind of block, we constructed the deep multibranch fusion residual network (DMF-ResNet). For evaluating the model performance, we first test our model on CIFAR-10 and CIFAR-100 benchmark data sets. The experimental results show that DMF-ResNet outperforms the baseline models significantly. Then, we construct DMF-ResNet with different depths for high-resolution image classification tasks and apply it to recognize insect pests. We evaluate the model performance on the IP102 data set, and the experimental results show that DMF-ResNet could achieve the best accuracy performance than the baseline models and other stateof- the-art methods. Based on these empirical experiments, we demonstrate the effectiveness of our approach. (Tokushima University Institutional Repository) ● Metadata: 116326 (Link to Publication Site) ● Publication site (DOI): 10.1109/TCDS.2020.2993060 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/TCDS.2020.2993060 (Tokushima University Institutional Repository: 116326, DOI: 10.1109/TCDS.2020.2993060)
28.	Yiming Tang, Witold Pedrycz and Fuji Ren : Granular symmetric implicational method, IEEE Transactions on Emerging Topics in Computational Intelligence, 1-14, 2021. (Link to Publication Site) ● Publication site (DOI): 10.1109/TETCI.2021.3100597 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/TETCI.2021.3100597 (DOI: 10.1109/TETCI.2021.3100597)
29.	Tian Chen, Hongfang Yin, Xiaohui Yuan, Yu Gu, Fuji Ren and Xiao Sun : Emotion recognition based on fusion of long short-term memory networks and SVMs, Digital Signal Processing, 1-10, 2021. (Summary) This paper proposes a multimodal fusion emotion recognition method based on Dempster-Shafer evidence theory, which includes electroencephalogram (EEG) and electrocardiogram (ECG). For EEG, we use the SVM classifier to classify features, and for ECG, we establish the corresponding Bi-directional Long Short-Term Memory network emotion recognition structure, which is fused with EEG classification results through the evidence theory. We selected 25 video clips with five emotions (happy, relaxed, angry, sad, and disgusted), and a total of 20 subjects participated in our emotional experiment. The experimental results prove that the performance of the multi-modal fusion model proposed in this paper is superior to the single-modal emotion recognition model. In the Arousal and Valance dimensions, the average accuracy is improved by 2.64% and 2.75% compared with the EEG signal-based emotion recognition model. Compared with the emotion recognition model based on the ECG signal, the accuracy is improved by 7.37% and 8.73%. (Link to Publication Site) ● Publication site (DOI): 10.1016/j.dsp.2021.103153 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1016/j.dsp.2021.103153 (DOI: 10.1016/j.dsp.2021.103153)
30.	Duo Feng and Fuji Ren : Data-Driven Channel Pruning towards Local Binary Convolution Inverse Bottleneck Network Based on Squeeze-and-Excitation Optimization Weights, Electronics, 1-14, 2021. (Summary) This paper proposed a model pruning method based on local binary convolution (LBC) and squeeze-and-excitation (SE) optimization weights. We first proposed an efficient deep separation convolution model based on the LBC kernel. By expanding the number of LBC kernels in the model, we have trained a larger model with better results, but more parameters and slower calculation speed. Then, we extract the SE optimization weight value of each SE module according to the data samples and score the LBC kernel accordingly. Based on the score of each LBC kernel corresponding to the convolution channel, we performed channel-based model pruning, which greatly reduced the number of model parameters and accelerated the calculation speed. The model pruning method proposed in this paper is verified in the image classification database. Experiments show that, in the model using the LBC kernel, as the number of LBC kernels increases, the recognition accuracy will increase. At the same time, the experiment also proved that the recognition accuracy is maintained at a similar level in the small parameter model after channel-based model pruning by the SE optimization weight value. (Tokushima University Institutional Repository) ● Metadata: 116521 (Link to Publication Site) ● Publication site (DOI): 10.3390/electronics10111329 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85106933886 (Tokushima University Institutional Repository: 116521, DOI: 10.3390/electronics10111329, Elsevier: Scopus)
31.	Min Hu, Peng Ge, Xiaohua Wang, Hui Lin and Fuji Ren : A spatio-temporal integrated model based on local and global features for video expression recognition, The Visual Computer, 1-18, 2021. (Link to Publication Site) ● Publication site (DOI): 10.1007/s00371-021-02136-z (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1007/s00371-021-02136-z (DOI: 10.1007/s00371-021-02136-z)
32.	Xiaohua Wang, Cong Yu, Yu Gu, Min Hu and Fuji Ren : Multi-Task and Attention Collaborative Network for Facial Emotion Recognition, IEEJ Transactions on Electrical and Electronic Engineering (TEEE), Vol.16, No.4, 568-576, 2021. (Summary) Facial expression is one of the most direct and effective ways to recognize emotions, widely used in human-computer interaction, affective computing, and other research fields. Expression recognition can be divided into discrete expression classification and continuous dimensional emotion recognition. Most of the existing multi-dimensional emotional estimation only considers the data under laboratory conditions. In this paper, facial emotion estimation is performed based on real-world images and combined with the advantages of multi-task learning and attention mechanism. We improve the multi-task attention network (MTAN) from two aspects: task and feature. At the aspect of the task, the multi-task collaborative attention network (MTCAN), which is based on task correlation, is proposed to solve task deviation in multi-task learning. At the aspect of the feature, based on MTCAN, we came up with MTACN, which used the self-attention mechanism to measure the importance of each attention module for each specific task. Then, we can capture the local-to-global connection in one step and fully exploit the feature within different levels of each task. Experimental results on the AffectNet dataset show that the performance of the model is significantly better than the original network, and the Root-mean-square error and consistency correlation coefficient results are superior to other existing models. (Link to Publication Site) ● Publication site (DOI): 10.1002/tee.23331 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1002/tee.23331 (DOI: 10.1002/tee.23331)
33.	Yokotani Tomoya, Tanioka Ryuichi, Kawai Chihiro, Betriana Feni, Hirokazu Ito, Yuko Yasuhara, Tetsuya Tanioka, Rozzano De Castro Locsin, Kazuyuki Matsumoto and Fuji Ren : Human Psychological Burden and Thinking Process while Operating a Humanoid Robot Conversation App Program, International Journal of Advanced Intelligence (IJAI), Vol.12, No.1, 23-35, 2021. (Keyword) Older adults / communication robot / Pepper robot / natural language processing / artificial intelligence / human thinking process / psychological burden
34.	Hirokazu Ito, Kazuyuki Matsumoto, XIN KANG, Tetsuya Tanioka, Yuko Yasuhara, Rozzano De Castro Locsin and Fuji Ren : The AI Development Through Transforming Tacit Knowledge to Explicit Knowledge of Nurses' Dialogue for Patients with Dementia, International Journal of Advanced Intelligence (IJAI), Vol.12, No.1, 11-21, 2021. (Keyword) natural language processing / artificial intelligence / dementia care / PsyNACS / explicit and tacit knowledge / nurses' dialogue / humanoid robot (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1010576118604664832 (CiNii: 1010576118604664832)
35.	Yuki Obayashi, Feni Betriana, Tetsuya Tanioka, Tomoya Yokotani, Ryuichi Tanioka, Chihiro Kawai, Hirokazu Ito, Yuko Yasuhara, Rozzano De Castro Locsin, Kyoko Osaka, Kazuyuki Matsumoto, Fuji Ren and Yoshihiro Kai : Developmental Issues of Communication for Robot Applications in Older People Care: An Integrative Review, International Journal of Advanced Intelligence (IJAI), Vol.12, No.1, 53-67, 2021. (Keyword) Communication robots / applications / performance of humanoid robots / developmental issues
36.	Jun Liu, Tingting Wang and Fuji Ren : Lock Isolation Security Architecture for Reconfigurable Scanning Networks, Journal of Computer-Aided Design & Computer Graphics, Vol.33, No.3, 1-7, 2021. (Summary) To protect the reconfigurable scanning network from the influence of unauthorized access, tampering of transmitted data by malicious instruments and sniffing, a lock isolation security structure is proposed. Firstly, the presented structure divides the instruments without security threat to each other into one group, and the groups can be accessed one by one via the isolated signals, which can prevent malicious instruments tampering and sniffing transmitted data. Secondly, the key instruments are protected by the lock segment insertion bit. The lock segment insertion bit can only be opened when multiple key values at specific positions are set to specific values (0, 1 sequence), which can increase the difficulty of unauthorized access. Besides, to reduce the hardware overhead, and the difficulty of place and route caused by excessive instrument groups, instrument grouping algorithm is proposed. The proposed algorithm firstly constructs an undirected graph based on the security relationship among instruments. Then the maximal independent sets of the undirected are obtained. In this way, the number of instrument groups is reduced greatly. Compared to other similar methodologies, the experimental results conducted on ITC 02 benchmark circuits show that the time consumption for opening the locking segment insertion bit of the proposed security structure increased by 7 times, and the average percentage reduction of area, power consumption and wire length is 3.81%, (Link to Publication Site) ● Publication site (DOI): 10.3724/SP.J.1089.2021.18447 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.3724/SP.J.1089.2021.18447 (DOI: 10.3724/SP.J.1089.2021.18447)
37.	Min Hu, Fei Qian, Dong Guo, Xiaohua Wang, Lei He and Fuji Ren : ETA-rPPGNet: Effective Time-Domain Attention Network for Remote Heart Rate Measurement, IEEE Transactions on Instrumentation and Measurement, Vol.70, 1-12, 2021. (Link to Publication Site) ● Publication site (DOI): 10.1109/TIM.2021.3058983 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/TIM.2021.3058983 (DOI: 10.1109/TIM.2021.3058983)
38.	Jiawen Deng and Fuji Ren : Hierarchical Network with Label Embedding for Contextual Emotion Recognition, Research : A Science Partner Journal, Vol.2021, No.1, 1-9, 2021. (Summary) Emotion recognition has been used widely in various applications such as mental health monitoring and emotional management. Usually, emotion recognition is regarded as a text classification task. Emotion recognition is a more complex problem, and the relations of emotions expressed in a text are nonnegligible. In this paper, a hierarchical model with label embedding is proposed for contextual emotion recognition. Especially, a hierarchical model is utilized to learn the emotional representation of a given sentence based on its contextual information. To give emotion correlation-based recognition, a label embedding matrix is trained by joint learning, which contributes to the final prediction. Comparison experiments are conducted on Chinese emotional corpus RenCECps, and the experimental results indicate that our approach has a satisfying performance in textual emotion recognition task. (Tokushima University Institutional Repository) ● Metadata: 116115 (Link to Publication Site) ● Publication site (DOI): 10.34133/2021/3067943 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.34133/2021/3067943 (Tokushima University Institutional Repository: 116115, DOI: 10.34133/2021/3067943)
39.	Ziyun Jiao and Fuji Ren : WRGAN: Improvement of RelGAN with Wasserstein Loss for Text Generation, Electronics, 1-14, 2021. (Summary) Generative adversarial networks (GANs) were rst proposed in 2014, and have been widely used in computer vision, such as for image generation and other tasks. However, the GANs used for text generation have made slow progress. One of the reasons is that the discriminator's guidance for the generator is too weak, which means that the generator can only get a ``true or false'' probability in return. Compared with the current loss function, the Wasserstein distance can provide more information to the generator, but RelGAN does not work well with Wasserstein distance in experiments. In this paper, we propose an improved neural network based on RelGAN and Wasserstein loss named WRGAN. Differently from RelGAN, we modi ed the discriminator network structure with 1D convolution of multiple different kernel sizes. Correspondingly, we also changed the loss function of the network with a gradient penalty Wasserstein loss. Our experiments on multiplepublicdatasetsshowthatWRGANoutperformsmostoftheexistingstate-of-the-artmethods, and the Bilingual Evaluation Understudy(BLEU) scores are improved with our novel method. (Tokushima University Institutional Repository) ● Metadata: 116296 (Link to Publication Site) ● Publication site (DOI): 10.3390/electronics10030275 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.3390/electronics10030275 (Tokushima University Institutional Repository: 116296, DOI: 10.3390/electronics10030275)
40.	Zhichao Cui, yaochen Li, Chi Zhang, Yuehu Liu and Fuji Ren : Coarse-to-Fine 3D Road Model Registration for Traffic Video Augmentation, IET Image Processing, 2020. (Link to Publication Site) ● Publication site (DOI): 10.1049/iet-ipr.2019.1036 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1049/iet-ipr.2019.1036 (DOI: 10.1049/iet-ipr.2019.1036)
41.	Fuji Ren and Yanwei Bao : A Review on Human-Computer Interaction and Intelligent Robots, International Journal of Information Technology & Decision Making, Vol.19, No.1, 5-47, 2020. (Summary) In the field of artificial intelligence, human computer interaction (HCI) technology and its related intelligent robot technologies are essential and interesting contents of research. From the perspective of software algorithm and hardware system, these abovementioned technologies study and try to build a natural HCI environment. The purpose of this research is to provide an overview of HCI and intelligent robots. This research highlights the existing technologies of listening, speaking, reading, writing, and other senses, which are widely used in human interaction. Based on these same technologies, this research introduces some intelligent robot systems and platforms. This paper also forecasts some vital challenges of researching HCI and intelligent robots. The authors hope that this work will help researchers in the field to acquire the necessary information and technologies to further conduct more advanced research. (Tokushima University Institutional Repository) ● Metadata: 115376 (Link to Publication Site) ● Publication site (DOI): 10.1142/S0219622019300052 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1142/S0219622019300052 (Tokushima University Institutional Repository: 115376, DOI: 10.1142/S0219622019300052)
42.	Fei Wang, Quan Wang, Feiping Ne, Zhongheng Li, Weizhong Yu and Fuji Ren : A linear multivariate binary decision tree classifier based on K-means splitting, Pattern Recognition, Vol.107, No.3, 1-13, 2020. (Summary) A novel linear multivariate decision tree classifier, Binary Decision Tree based on K-means Splitting (BDTKS), is presented in this paper. The unsupervised K-means clustering is recursively integrated into the binary tree, building a hierarchical classifier. The introduction of the unsupervised K-means clustering provides the powerful generalization ability for the resulting BDTKS model. Then, the good generalization ability of BDTKS ensures the classification performance. A novel non-split condition with an easy-setting hyperparameter which focuses more on minority classes of the current node is proposed and applied in the BDTKS model, avoiding ignoring the minority classes in the class imbalance cases. Furthermore, the K-means centroid based BDTKS model is converted into the hyperplane based decision tree, speeding up the process of classification. Extensive experiments on the publicly available data sets have demonstrated that the proposed BDTKS matches or outperforms the previous decision trees. (Link to Publication Site) ● Publication site (DOI): 10.1016/j.patcog.2020.107521 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1016/j.patcog.2020.107521 (DOI: 10.1016/j.patcog.2020.107521)
43.	wenjie Liu, Wu Guoqing, Fuji Ren and XIN KANG : DFF-ResNet: An Insect Pest Recognition Model based on Residual Networks, Big Data Mining and Analytics, Vol.3, No.4, 300-310, 2020. (Tokushima University Institutional Repository) ● Metadata: 115879 (Link to Publication Site) ● Publication site (DOI): 10.26599/BDMA.2020.9020021 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.26599/BDMA.2020.9020021 (Tokushima University Institutional Repository: 115879, DOI: 10.26599/BDMA.2020.9020021)
44.	Jiawen Deng and Fuji Ren : Multi-label Emotion Detection via Emotion-Specified Feature Extraction and Emotion Correlation Learning, IEEE Transactions on Affective Computing, Vol.8, No.1, 2020. (Summary) Textual emotion detection is an attractive task while previous studies mainly focused on polarity or single-emotion classification. However, human expressions are complex, and multiple emotions often co-occur with non-negligible emotion correlations. In this paper, a Multi-label Emotion Detection Architecture (MEDA) is proposed to detect all associated emotions expressed in a given piece of text. MEDA is mainly composed of two modules: Multi-Channel Emotion-Specified Feature Extractor (MC-ESFE) and Emotion Correlation Learner (ECorL). MEDA captures underlying emotion-specified features through MC-ESFE module, which is composed of multiple channel-wise ESFE networks. Each channel in MC-ESFE is devoted to the feature extraction of a specified emotion from sentence-level to context-level through a hierarchical structure. With underlying features, emotion correlation learning is implemented through an emotion sequence predictor in ECorL. Furthermore, we define a new loss function: multi-label focal loss. With this loss function, the model can focus more on misclassified positive-negative emotion pairs and improve the overall performance by balancing the prediction of positive and negative emotions. The evaluation of proposed MEDA architecture is carried out on emotional corpus: RenCECps and NLPCC2018 datasets. The experimental results indicate that the proposed method can achieve better performance than state-of-the-art methods in this task. (Tokushima University Institutional Repository) ● Metadata: 115391 (Link to Publication Site) ● Publication site (DOI): 10.1109/TAFFC.2020.3034215 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/TAFFC.2020.3034215 (Tokushima University Institutional Repository: 115391, DOI: 10.1109/TAFFC.2020.3034215)
45.	Yindong Dong and Fuji Ren : Multi-reservoirs EEG signal feature sensing and recognition method based on generative adversarial networks, Computer Communications, Vol.164, 177-184, 2020. (Summary) EEG emotion recognition is one of the interesting and challenging tasks in the research based emotion human computer interface system. In this paper, a multi-reservoirs feature coding continuous label fusion semi-supervised Generative Adversarial Networks (MCLFS-GAN) is proposed by using permutation phase transfer entropy as the EEG signal feature. Firstly, the obtained features are encapsulated in time series, and then the features are sent into multi-reservoirs according to the division of brain intra, brain interval or frequency band. After convolution optimization, the feature expression with time sequence relationship is obtained. The generic representation between the features and pseudo effective feature expression are iteratively learned in encoder E and generator G in the generative adversarial way. In addition, the continuous fusion for class intra tags can help to form continuous differences between classes. The experimental results show that the accuracy for the four classification is 81.32% and 54.87% respectively by using SAP and LOSO in DEAP database. Compared with other models, this algorithm can effectively improve the recognition performance. (Link to Publication Site) ● Publication site (DOI): 10.1016/j.comcom.2020.10.004 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1016/j.comcom.2020.10.004 (DOI: 10.1016/j.comcom.2020.10.004)
46.	Zhong Huang, Fuji Ren, Min Hu and Sugen Chen : Facial Expression Imitation Method for Humanoid Robot Based on Smooth-Constraint Reversed Mechanical Model (SRMM), IEEE Transactions on Human-Machine Systems, Vol.50, No.6, 538-549, 2020. (Summary) To improve the space time similarity and motion smoothness of facial expression imitation (FEI), a real-time FEI method for a humanoid robot is proposed based on smooth-constraint reversed mechanical model (SRMM) by combining a sequence-to-sequence deep learning model and a motion-smoothing constraint. First, on the basis of facial data from a Kinect capture device, a facial feature vector is characterized based on 3 head postures, 17 facial animation units, and facial geometric deformation cascaded by Laplace coordinates. Second, a reversed mechanical model is constructed via a multilayer long short-term memory neural network to accomplish direct mapping from facial feature sequences to motor position sequences. Additionally, to overcome the motor chattering phenomenon during real-time FEI, a high-order polynomial is constructed to fit the position sequence of motors, and an SRMM is proposed and designed based on the deviation of position, velocity, and acceleration. Finally, aiming to imitate the real-time facial feature sequences of a performer captured from Kinect, the optimal position sequences generated based on the SRMM is sent to the hardware system to keep the space time characteristics consistent with those of the performer. The experimental results demonstrate that the motor position deviation of the SRMM is less than 8%. The space time similarity between the robot and the performer is greater than 85%, and the motion smoothness of the online FEI exceeded 90%. Compared with other related methods, the proposed method achieves a remarkable improvement in motor position deviation, space time similarity, and motion smoothness. (Link to Publication Site) ● Publication site (DOI): 10.1109/THMS.2020.3017781 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/THMS.2020.3017781 (DOI: 10.1109/THMS.2020.3017781)
47.	Tian Chen, Mingyan Fan, Fuji Ren and Hongfang Yin : Emotion recognition using pupil position, Application Research of Computers, Vol.38, No.5, 1-6, 2020. (Link to Publication Site) ● Publication site (DOI): 10.19734/j.issn.1001-3695.2020.06.0165 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.19734/j.issn.1001-3695.2020.06.0165 (DOI: 10.19734/j.issn.1001-3695.2020.06.0165)
48.	Tian Chen, Sihang Ju, Fuji Ren, Minhyan Fan and Yu Gu : EEG emotion recognition model based on the LIBSVM classifier, Measurement, Vol.164, 1-7, 2020. (Summary) This paper proposes an electroencephalogram(EEG) emotion recognition method based on the LIBSVM classifier. EEG features are calculated to represent the characterisitics associated with emotion states. First calculating the Lempel Ziv complexity and wavelet detail coefficients for the pre-processed EEG signals; then obtaining the co-integration relationship that reflecting the relationship between channels according to the cointegration test; next performing Empirical Mode Decomposition(EMD) on the pre-processed EEG signals; finally calculating the average approximate entropy of the first four Intrinsic Mode Functions(IMFs). The calculated four features are input into the LIBSVM classifier to realize the sentiment classification of each channel data, and then the classification results of each channel are fused by the Takagi Sugeno fuzzy model to achieve the final emotion classification. The experimental results show that when the two-category classifications are performed on Arousal and Valance, the average sentiment recognition rates are 74.88% and 82.63%, respectively. (Link to Publication Site) ● Publication site (DOI): 10.1016/j.measurement.2020.108047 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85086700562 (DOI: 10.1016/j.measurement.2020.108047, Elsevier: Scopus)
49.	Degen Huang, Anil Ahmed, Yasser Syed Arafat, Iftekhar Khawaja Rashid, Qasim Abbas and Fuji Ren : Sentence-Embedding and Similarity via Hybrid Bidirectional-LSTM and CNN Utilizing Weighted-Pooling Attention, IEICE Transactions on Information and Systems, Vol.E103-D, No.10, 2216-2227, 2020. (Summary) Neural networks have received considerable attention in sentence similarity measuring systems due to their efficiency in dealing with semantic composition. However, existing neural network methods are not sufficiently effective in capturing the most significant semantic information buried in an input. To address this problem, a novel weighted-pooling attention layer is proposed to retain the most remarkable attention vector. It has already been established that long short-term memory and a convolution neural network have a strong ability to accumulate enriched patterns of whole sentence semantic representation. First, a sentence representation is generated by employing a siamese structure based on bidirectional long short-term memory and a convolutional neural network. Subsequently, a weighted-pooling attention layer is applied to obtain an attention vector. Finally, the attention vector pair information is leveraged to calculate the score of sentence similarity. An amalgamation of both, bidirectional long short-term memory and a convolutional neural network has resulted in a model that enhances information extracting and learning capacity. Investigations show that the proposed method outperforms the state-of-the-art approaches to datasets for two tasks, namely semantic relatedness and Microsoft research paraphrase identification. The new model improves the learning capability and also boosts the similarity accuracy as well. (Link to Publication Site) ● Publication site (DOI): 10.1587/transinf.2018EDP7410 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1587/transinf.2018EDP7410 (DOI: 10.1587/transinf.2018EDP7410)
50.	Jiaqiao Zhang, XIN KANG, Hongjun Ni and Fuji Ren : Surface defect detection of steel strips based on classification priority YOLOv3-dense network, Ironmaking and Steelmaking, Vol.8, 1-12, 2020. (Summary) The steel strip is an essential raw material in the machinery industry. Besides, the surface defects of the steel strip directly determine its performance. To achieve rapid and effective detection of the defects, a CP-YOLOv3-dense (classification priority YOLOv3 DenseNet) neural network was proposed in the present study. The model used YOLOv3 as basic network, implemented priority classification on the images, and then replaced the two residual network modules with two dense network modules. Therefore, the network can receive the multi-layer convolution features output by the dense connection block before making predictions, consequently enhancing the reuse and fusion of features. Finally, the six kinds of surface defects were detected by the improved network. According to the results, the detection precision of the CP-YOLOv3-dense network is 85.7%, the recall rate is 82.3%, the mean average precision is 82.73%, and the detection time of each image is 9.68 ms. (Keyword) Steel strip / defect detection / deep learning / neural network model / surface technology (Tokushima University Institutional Repository) ● Metadata: 115375 (Link to Publication Site) ● Publication site (DOI): 10.1080/03019233.2020.1816806 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85091091649 (Tokushima University Institutional Repository: 115375, DOI: 10.1080/03019233.2020.1816806, Elsevier: Scopus)
51.	XIAOHUA WANG, JIANQIAO GONG, MIN HU, YU GU and Fuji Ren : LAUN Improved StarGAN for Facial Emotion Recognition, IEEE Access, Vol.8, No.1, 161509-161518, 2020. (Summary) In the eld of facial expression recognition, deep learning is extensively used. However, insuf cient and unbalanced facial training data in available public databases is a major challenge for improving the expression recognition rate. Generative Adversarial Networks (GANs) can produce more one-to-onefaceswithdifferentexpressions,whichcanbeusedtoenhancedatabases.StarGANcanperform one-to-many translations for multiple expressions. Compared with original GANs, StarGAN can increase the ef ciency of sample generation. Nevertheless, there are some defects in essential areas of the generated face,suchasthemouthandthefuzzysidefaceimagegeneration.Toaddresstheselimitations,weimproved StarGAN to alleviate the defects of images generation by modifying the reconstruction loss and adding the Contextual loss. Meanwhile, we added the Attention U-Net to StarGAN's generator, replacing StarGAN's original generator. Therefore, we proposed the Contextual loss and Attention U-Net (LAUN) improved StarGAN.TheU-shapestructureandskipconnectioninAttentionU-Netcaneffectivelyintegratethedetails and semantic features of images. The network's attention structure can pay attention to the essential areas of the human face. The experimental results demonstrate that the improved model can alleviate some aws in the face generated by the original StarGAN. Therefore, it can generate person images with better quality withdifferentposesandexpressions.TheexperimentswereconductedontheKarolinskaDirectedEmotional Facesdatabase,andtheaccuracyoffacialexpressionrecognitionis95.97%,2.19%higherthanthatbyusing StarGAN. Meanwhile, the experiments were carried out on the MMI Facial Expression Database, and the accuracy of expression is 98.30%, 1.21% higher than that by using StarGAN. Moreover, experiment results have better performance based on the LAUN improved StarGAN enhanced databases than those without enhancement. (Tokushima University Institutional Repository) ● Metadata: 116332 (Link to Publication Site) ● Publication site (DOI): 10.1109/ACCESS.2020.3021531 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/ACCESS.2020.3021531 (Tokushima University Institutional Repository: 116332, DOI: 10.1109/ACCESS.2020.3021531)
52.	Yangyang Zhou and Fuji Ren : CERG: Chinese Emotional Response Generator with Retrieval Method, Research : A Science Partner Journal, Vol.2020, No.1, 1-8, 2020. (Summary) The dialogue system has always been one of the important topics in the domain of artificial intelligence. So far, most of the mature dialogue systems are task-oriented based, while non-task-oriented dialogue systems still have a lot of room for improvement. We propose a data-driven non-task-oriented dialogue generator ``CERG'' based on neural networks. This model has the emotion recognition capability and can generate corresponding responses. The data set we adopt comes from the NTCIR-14 STC-3 CECG subtask, which contains more than 1.7 million Chinese Weibo post-response pairs and 6 emotion categories. We try to concatenate the post and the response with the emotion, then mask the response part of the input text character by character to emulate the encoder-decoder framework. We use the improved transformer blocks as the core to build the model and add regularization methods to alleviate the problems of overcorrection and exposure bias. We introduce the retrieval method to the inference process to improve the semantic relevance of generated responses. The results of the manual evaluation show that our proposed model can make different responses to different emotions to improve the human-computer interaction experience. This model can be applied to lots of domains, such as automatic reply robots of social application. (Tokushima University Institutional Repository) ● Metadata: 116250 (Link to Publication Site) ● Publication site (DOI): 10.34133/2020/2616410 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.34133/2020/2616410 (Tokushima University Institutional Repository: 116250, DOI: 10.34133/2020/2616410)
53.	Jun Liu, Xiuyun Wang and Fuji Ren : Test Strategy for 2.5D ICs Using Auxiliary Interposer and E-fuses, Computer Engineering and Applications, Vol.39, No.6, 1863-1868, 2020. (Link to Publication Site) ● Publication site (DOI): 10.3778/j.issn.1002-8331.1902-0035 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.3778/j.issn.1002-8331.1902-0035 (DOI: 10.3778/j.issn.1002-8331.1902-0035)
54.	Zheng Liu, XIN KANG, Shun Nishide and Fuji Ren : Vowel priority lip matching scheme and similarity evaluation model based on humanoid robot Ren-Xin, Journal of Ambient Intelligence and Humanized Computing, 2020. (Tokushima University Institutional Repository) ● Metadata: 118255 (Link to Publication Site) ● Publication site (DOI): 10.1007/s12652-020-02175-9 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85086366472 (Tokushima University Institutional Repository: 118255, DOI: 10.1007/s12652-020-02175-9, Elsevier: Scopus)
55.	Leyuan Jia, Yu Gu, Ken Cheng, Huan Yan and Fuji Ren : BeAware: Convolutional neural network(CNN) based user behavior understanding through WiFi channel state information, Neurocomputing, Vol.397, 457-463, 2020. (Summary) In modern informatics society, human beings are becoming more and more attached to the computer. Therefore, understanding user behavior is critical to various application elds like sedentary analysis, human-computer interaction, and affective computing. Current sensor-based and vision-based user behavior understanding approaches are either contact or obtrusive to users, jeopardizing their availability and practicality. To this end, we present BeAware, a contactless Radio Frequency (RF) based user behavior understanding system leveraging the WiFi Channel State Information (CSI). The key idea is to visualize the channel data affected by human movements into time-series heat-map images, which are processed by a Convolutional Neural Network (CNN) to understand the corresponding user behaviors. We prototype BeAware on commodity low-cost WiFi devices and evaluate its performance in real-world environments. Experimental results have veri ed its effectiveness in recognizing user behaviors. (Link to Publication Site) ● Publication site (DOI): 10.1016/j.neucom.2019.09.111 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1016/j.neucom.2019.09.111 (DOI: 10.1016/j.neucom.2019.09.111)
56.	Yu Gu, Yantong Wang, Tao Liu, Yusheng Ji, Zhi Liu, Peng Li, Xiaoyan Wang, Xin Ai and Fuji Ren : EmoSense: Computational Intelligence Driven Emotion Sensing via Wireless Channel Data, IEEE Transactions on Emerging Topics in Computational Intelligence, Vol.4, No.3, 216-226, 2020. (Summary) Emotion is well recognized as a distinguished symbol ofhumanbeings,anditplaysacrucialroleinourdailylives.Existingvision-basedorsensor-basedsolutionsareeitherobstructiveto use or rely on specialized hardware, hindering their applicability. This paper introduces EmoSense, a rst-of-its-kind wireless emotionsensingsystemdrivenbycomputationalintelligence.Thebasic methodologyistoexplorethephysicalexpressionofemotionsfrom wireless channel response via data mining. The design and implementation of EmoSense faces two major challenges extracting physical expression from wireless channel data and recovering emotion from the corresponding physical expression. For the former, we present a Fresnel zone-based theoretical model depicting the ngerprint of the physical expression on channel response. For the latter, we design an ef cient computational intelligence driven mechanism to recognize emotion from the corresponding ngerprints.WeprototypedEmoSenseonthecommodityWiFiinfrastructure and compared it with mainstream sensor-based and vision-basedapproachesinthereal-worldscenario.Thenumerical study over 3360 cases con rms that EmoSense achieves a comparable performance to the vision-based and sensor-based rivals under different scenarios. EmoSense only leverages the low-cost and prevalent WiFi infrastructures and thus, constitutes a tempting solution for emotion sensing. (Link to Publication Site) ● Publication site (DOI): 10.1109/TETCI.2019.2902438 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/TETCI.2019.2902438 (DOI: 10.1109/TETCI.2019.2902438)
57.	Yu Gu, Jinhai Zhan, Jie Li, Yusheng Ji, Xin An and Fuji Ren : Sleepy: Wireless Channel Data Driven Sleep Monitoring via Commodity WiFi Devices, IEEE Transactions on Big Data, Vol.6, No.2, 258-268, 2020. (Summary) Sleep is a major event of our daily lives. Its quality constitutes a critical indicator of people's health conditions, both mentally and physically. Existing sensor-based or vision-based sleep monitoring systems either are obstructive to use or fail to provide adequate coverage. With the fast expansion of wireless infrastructures nowadays, channel data, which is pervasive and transparent, emerges as another alternative. To this end, we propose Sleepy, a wireless channel data driven sleep monitoring system leveraging commercial WiFi devices. The key idea of Sleepy is that the energy feature of the wireless channel follows a Gaussian Mixture Model (GMM) derived from the accumulated channel data over a long period. Therefore, a GMM based foreground extraction method has been designed to adaptively distinguish motions like rollovers (foreground) from background (stationary postures), leading to certain major merits, e.g., no calibrations or target-dependent training needed. We prototype Sleepy and evaluate it in two real environments. In the short-term controlled experiments, Sleepy achieves 95.04% detection accuracy and 4.07% false negative rate. In the 60-minute real case studies, Sleepy demonstrates strong stability. Considering that Sleepy is compatible with existing WiFi infrastructure, it constitutes a low-cost yet promising solution for sleep monitoring. (Link to Publication Site) ● Publication site (DOI): 10.1109/TBDATA.2018.2851201 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/TBDATA.2018.2851201 (DOI: 10.1109/TBDATA.2018.2851201)
58.	Fuji Ren and Siyuan Xue : Intention Detection Based on Siamese Neural Network With Triplet Loss, IEEE Access, Vol.8, No.1, 82242-82254, 2020. (Summary) Understanding the user's intention is an essential task for the spoken language understanding (SLU) module in the dialogue system, which further illustrates vital information for managing and generating future action and response. In this paper, we propose a triplet training framework based on the multiclassclassi cationapproachtoconductthetrainingfortheintentiondetectiontask.Precisely,weutilize aSiameseneuralnetworkarchitecturewithmetriclearningtoconstructarobustanddiscriminativeutterance feature embedding model. We modi ed the RMCNN model and ne-tuned BERT model as Siamese encoderstotrainutterancetripletsfromdifferentsemanticaspects.Thetripletlosscaneffectivelydistinguish the details of two input data by learning a mapping from sequence utterances to a compact Euclidean space. After generating the mapping, the intention detection task can be easily implemented using standard techniques with pre-trained embeddings as feature vectors. Besides, we use the fusion strategy to enhance utterance feature representation in the downstream of intention detection task. We conduct experiments on several benchmark datasets of intention detection task: Snips dataset, ATIS dataset, Facebook multilingual task-oriented datasets, Daily Dialogue dataset, and MRDA dataset. The results illustrate that the proposed methodcaneffectivelyimprovetherecognitionperformanceofthesedatasetsandachievesnewstate-of-theart results on single-turn task-oriented datasets (Snips dataset, Facebook dataset), and a multi-turn dataset (Daily Dialogue dataset). (Tokushima University Institutional Repository) ● Metadata: 115374 (Link to Publication Site) ● Publication site (DOI): 10.1109/ACCESS.2020.2991484 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85084957800 (Tokushima University Institutional Repository: 115374, DOI: 10.1109/ACCESS.2020.2991484, Elsevier: Scopus)
59.	Siyuan Xue and Fuji Ren : Knowledge Graph based Question and Answer System for Cosmetic Domain, International Journal of Advanced Intelligence (IJAI), Vol.11, No.1, 15-28, 2020. (Tokushima University Institutional Repository) ● Metadata: 116151 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1572261552535245952 (Tokushima University Institutional Repository: 116151, CiNii: 1572261552535245952)
60.	Fuji Ren and Qian Zhang : An Emotion Expression Extraction Method for Chinese Microblog Sentences, IEEE Access, Vol.8, No.1, 69244-69255, 2020. (Summary) With the rapid spread of Chinese microblog, a large number of microblog topics are being generated in real-time. More and more users pay attention to emotion expressions of these opinionated sentences in different topics. It is challenging to label the emotion expressions of opinionated sentences manually. For this endeavor, an emotion expression extraction method is proposed to process millions of user-generated opinionated sentences automatically in this paper. Specifically, the proposed method mainly contains two tasks: emotion classification and opinion target extraction. We first use a lexicon-based emotion classification method to compute different emotion values in emotion label vectors of opinionated sentences. Then emotion label vectors of opinionated sentences are revised by an unsupervised emotion label propagation algorithm. After extracting candidate opinion targets of opinionated sentences, the opinion target extraction task is performed on a random walk-based ranking algorithm, which considers the connection between candidate opinion targets and the textual similarity between opinionated sentences, ranks candidate opinion targets of opinionated sentences. Experimental results demonstrate the effectiveness of algorithms in the proposed method. (Tokushima University Institutional Repository) ● Metadata: 115139 (Link to Publication Site) ● Publication site (DOI): 10.1109/ACCESS.2020.2985726 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85083997665 (Tokushima University Institutional Repository: 115139, DOI: 10.1109/ACCESS.2020.2985726, Elsevier: Scopus)
61.	Yu Zhao, Anxiang Zhang, Huali Feng, Qing Li, Patrick Gallinari and Fuji Ren : Knowledge graph entity typing via learning connecting embeddings, Knowledge-based Systems, No.1, 2020. (Summary) Knowledge graph (KG) entity typing aims at inferring possible missing entity type instances in KG, which is a very significant but still under-explored subtask of knowledge graph completion. In this paper, we propose a novel approach for KG entity typing which is trained by jointly utilizing local typing knowledge from existing entity type assertions and global triple knowledge in KGs. Specifically, we present two distinct knowledge-driven effective mechanisms of entity type inference. Accordingly, we build two novel embedding models to realize the mechanisms. Afterward, a joint model via connecting them is used to infer missing entity type instances, which favors inferences that agree with both entity type instances and triple knowledge in KGs. Experimental results on two real-world datasets (Freebase and YAGO) demonstrate the effectiveness of our proposed mechanisms and models for improving KG entity typing. (Link to Publication Site) ● Publication site (DOI): 10.1016/j.knosys.2020.105808 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85082527535 (DOI: 10.1016/j.knosys.2020.105808, Elsevier: Scopus)
62.	Fuji Ren and Yangyang Zhou : CGMVQA: A New Classification and Generative Model for Medical Visual Question Answering, IEEE Access, Vol.8, No.1, 50626-50636, 2020. (Summary) Medical images are playing an important role in the medical domain. A mature medical visual question answering system can aid diagnosis, but there is no satisfactory method to solve this comprehensive problem so far. Considering that there are many different types of questions, we propose a model called CGMVQA, including classification and answer generation capabilities to turn this complex problem into multiple simple problems in this paper. We adopt data augmentation on images and tokenization on texts. We use pre-trained ResNet152 to extract image features and add three kinds of embeddings together to deal with texts. We reduce the parameters of the multi-head self-attention transformer to cut the computational cost down. We adjust the masking and output layers to change the functions of the model. This model establishes new state-of-the-art results: 0.640 of classification accuracy, 0.659 of word matching and 0.678 of semantic similarity in ImageCLEF 2019 VQA-Med data set. It suggests that the CGMVQA is effective in medical visual question answering and can better assist doctors in clinical analysis and diagnosis. (Tokushima University Institutional Repository) ● Metadata: 115141 (Link to Publication Site) ● Publication site (DOI): 10.1109/ACCESS.2020.2980024 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/ACCESS.2020.2980024 (Tokushima University Institutional Repository: 115141, DOI: 10.1109/ACCESS.2020.2980024)
63.	Xiuyun Wang, Jun Liu and Fuji Ren : TSVs crosstalk fault grouping test and diagnostic strategy, MICROELECTRONICS & COMPUTER, Vol.37, No.2, 30-36, 2020. (Link to Publication Site) ● Publication site (DOI): 10.19304/j.cnki.issn1000-7180.2020.02.006 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.19304/j.cnki.issn1000-7180.2020.02.006 (DOI: 10.19304/j.cnki.issn1000-7180.2020.02.006)
64.	Tian Chen, Yang Zhou, Fuji Ren, Xin An and Huyin Zhao : Improved run-length codes compression method based on tri-state signal, Computer Engineering, 1-8, 2020. (Link to Publication Site) ● Publication site (DOI): 10.19678/j.issn.1000-3428.0057157 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.19678/j.issn.1000-3428.0057157 (DOI: 10.19678/j.issn.1000-3428.0057157)
65.	OMAR AHMED, Fuji Ren, AMMAR HAWBANI and YASER AL-SHARABI : Energy Optimized Congestion Control Based Temperature Aware Routing Algorithm For Software Defined Wireless Body Area Networks, IEEE Access, Vol.8, 41085-41099, 2020. (Summary) Wireless Body Area Network(WBAN) is a promising cost-effective technology for the privacy con ned military applications and healthcare applications like remote health monitoring, telemedicine, and e-health services. The use of a Software-De ned Network (SDN) approach improves the control and management processes of the complex structured WBANs and also provides higher exibility and dynamic network structure. To seamless routing performance in SDN-based WBAN, the energy-ef ciency problems must be tackled effectively. The main contribution of this paper is to develop a novel Energy Optimized Congestion Control based on Temperature Aware Routing Algorithm (EOCC-TARA) using Enhanced Multi-objective Spider Monkey Optimization (EMSMO) for SDN-based WBAN. This algorithm overcomes the vital challenges, namely energy-ef ciency, congestion-free communication, and reducing adverse thermal effectsin WBAN routing. First,the proposed EOCC-TARA routing algorithm considers the effects of temperature due to the thermal dissipation of sensor nodes and formulates a strategy to adaptively select the forwarding nodes based on temperature and energy. Then the congestion avoidance concept is added with the energy-ef ciency, link reliability, and path loss for modeling the cost function based on which the EMSMO provides the optimal routing. Simulations were performed, and the evaluation results showed that the proposed EOCC-TARA routing algorithm has superior performance than the traditional routing approaches in terms of energy consumption, network lifetime, throughput, temperature control, congestion overhead, delay, and successful transmission rate. (Tokushima University Institutional Repository) ● Metadata: 115144 (Link to Publication Site) ● Publication site (DOI): 10.1109/ACCESS.2020.2976819 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/ACCESS.2020.2976819 (Tokushima University Institutional Repository: 115144, DOI: 10.1109/ACCESS.2020.2976819)
66.	Xiaohua Wang, Lijuan Pan, Muzi Peng, Min Hu, Chunhua Jin and Fuji Ren : Video Emotion Recognition Based on Hierarchical Attention Model, Journal of Computer-Aided Design & Computer Graphics, Vol.32, No.1, 27-35, 2020. (Summary) LSTM network is widely used in facial expression recognition of video sequences. In view of the limited representation ability of single-layer LSTM and the limitation of its generalization ability when solving complex problems, a hierarchical attention model is proposed. Hierarchical representation of time series data is learned by stacking LSTM, self-attention mechanism is used to construct differentiated hierarchical relationships, and a penalty term is constructed and further combined with the loss function to optimize the network performance. Experiments on CK+ and MMI datasets, demonstrate that due to the construction of good hierarchical features, each step in time series can select information from the more interesting feature hierarchy. Compared with ordinary single-layer LSTM, hierarchical attention model can express the emotional information of video sequences more effectively. (Link to Publication Site) ● Publication site (DOI): 10.3724/SP.J.1089.2020.17719 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85080026347 (DOI: 10.3724/SP.J.1089.2020.17719, Elsevier: Scopus)
67.	Zhichao Cui, Yuehu Liu and Fuji Ren : Homography-based traffic sign localisation and pose estimation from image sequence, IET Image Processing, Vol.13, No.14, 2829-2839, 2019. (Summary) This study proposes a vision-based method for traffic sign attribute estimation, i.e. 3D position and pose, from image sequences by binocular or monocular cameras. The method starts with acquiring robust feature correspondences based on homography constraints from image pairs. Then the objective function is designed to integrate the feature correspondences to optimise the parameters of the traffic sign plane in the 3D coordinate. Finally, the sign plane is utilised for attribute estimation. In addition, the authors provide an extension for the raw KITTI dataset, which can be utilised for 3D tasks of traffic sign localisation and pose estimation. In the experiments, three popular methods are employed for comparisons based on the publicly available BelgiumTS and KITTI datasets. The results show that the authors' method based on SIFT and SURF features can locate the traffic signs with a mean error of ∼0.44 and 0.51 m in the BelgiumTS and KITTI datasets, respectively, and estimate the pose with a mean error of ∼14.45° in the KITTI dataset. (Link to Publication Site) ● Publication site (DOI): 10.1049/iet-ipr.2019.0023 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1049/iet-ipr.2019.0023 (DOI: 10.1049/iet-ipr.2019.0023)
68.	Xiaohua Wang, Muzi Peng, Lijuan Pan, MIn Hu, Chunhua Jin and Fuji Ren : Two-Level Attention with Multi-task Learning for Facial Emotion Estimation, Lecture Notes in Computer Science, Vol.11295, 227-238, 2019. (Link to Publication Site) ● Publication site (DOI): 10.1007/978-3-030-05710-7_19 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85059845886 (DOI: 10.1007/978-3-030-05710-7_19, Elsevier: Scopus)
69.	Hongjun Ni, Jiaqiao Zhang, Nansheng Zhao, Chusen Wang, Shuaishuai Lv, Fuji Ren and Xingxing Wang : Design on the Winter Jujubes Harvesting and Sorting Device, Applied Sciences, No.1, 1-17, 2019. (Summary) According to the existing problems of winter jujube harvesting, such as the intensive labor of manual picking, damage to the surface of winter jujubes, a winter jujube harvesting and sorting device was developed. This device consisted of vibration mechanism, collection mechanism, and sorting mechanism. The eccentric vibration mechanism made the winter jujubes fall, and the umbrella collecting mechanism can collect winter jujube and avoid the impact of winter jujube on the ground, and the sorting mechanism removed jujube leaves and divided the jujube into two types, and the automatic leveling mechanism made the device run smoothly in the field. Through finite element analysis and BP (Back Propagation) neural network analysis, the results show that: The vibration displacement of jujube tree is related to the trunk diameter and vibration position; the impact force of winter jujubes falling is related to the elastic modulus of umbrella material; the collecting area can be increased four times for each additional step of the collection mechanism; jujube leaves can be effectively removed when blower wind speed reaches 45.64 m/s. According to the evaluation standard grades of the jujubes harvesting and sorting, the device has good effects and the excellent rate up to 90%, which has good practicability and economy. (Keyword) winter jujube / harvesting and sorting / vibration mechanism / automatic leveling (Tokushima University Institutional Repository) ● Metadata: 114991 (Link to Publication Site) ● Publication site (DOI): 10.3390/app9245546 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.3390/app9245546 (Tokushima University Institutional Repository: 114991, DOI: 10.3390/app9245546)
70.	Tian Chen, Yongsheng Zuo, Xin An and Fuji Ren : A variable-length compatible compression scheme based on tristate signals, The Journal of Supercomputing, 1-14, 2019. (Summary) The test data volume for the manufacturing test of chips is increasing rapidly. This is due to the fact that the complexity of these chips is increasing rapidly and the transistor count is increasing exponentially. Aimed at solving the problems of large test data volume and long test time in chips test, this paper presents a deterministic test-based compression method that uses tristate signals encoding and compatible test cube merging. Firstly, the partial input reduction is carried out for the original test set. The proportion of ``don't care'' bits in the original test set is increased by merging compatible or inversely compatible inputs in the test cubes, so the compatibility among the test cubes is improved. Then, the test set is compressed and encoded by using tristate signal. Each test cube is divided into several data segments, which are encoded by tristate signals and multiple compatibility rules. This scheme can improve the compression ratio of the test set. The experimental results show that the proposed scheme achieves a good compression ratio, without excessive test power and area overhead. The average test compression ratio can reach 82.15%. (Link to Publication Site) ● Publication site (DOI): 10.1007/s11227-019-03071-6 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85075200794 (DOI: 10.1007/s11227-019-03071-6, Elsevier: Scopus)
71.	Jun Liu, Peng Dong and Fuji Ren : Diagonal-based for TSV Fault Tolerance Design, Microelectronics & Computer, 2019. (Summary) Three dimensional integrated circuits, using through-silicon vias(TSVs) as the communication link between vertical chip, with the advantages of high density, high bandwidth and low power consumption. As the TSV during processing and using process may be failure, will lead to the entire three-dimensional chip failure. In order to improve the yield of 3D chips, the yield of TSV must be raised as much as possible. This paper presents a novel diagonal-based redundant TSV repair scheme and proposes a repair algorithm based on maximum flow algorithm to tolerance the faulty TSV with redundant TSVs in the diagonal to improve the yield of the entire three-dimensional chip. Experimental results show that the yield of the proposed repair strategy is 98.38% to 98.96% and the hardware overhead can be reduced by up to 70% compared to routerbased technique.
72.	Xinyu He, Lishuang Li, Xingchen Song, Degen Huang and Fuji Ren : Multi-Level Attention Based BLSTM Neural Network for Biomedical Event Extraction, IEICE Transactions on Information and Systems, Vol.E102-D, No.9, 1842-1850, 2019. (Summary) Biomedical event extraction is an important and challenging task in Information Extraction, which plays a key role for medicine research and disease prevention. Most of the existing event detection methods are based on shallow machine learning methods which mainly rely on domain knowledge and elaborately designed features. Another challenge is that some crucial information as well as the interactions among words or arguments may be ignored since most works treat words and sentences equally. Therefore, we employ a Bidirectional Long Short Term Memory (BLSTM) neural network for event extraction, which can skip handcrafted complex feature extraction. Furthermore, we propose a multi-level attention mechanism, including word level attention which determines the importance of words in a sentence, and the sentence level attention which determines the importance of relevant arguments. Finally, we train dependency word embeddings and add sentence vectors to enrich semantic information. The experimental results show that our model achieves an F-score of 59.61% on the commonly used dataset (MLEE) of biomedical event extraction, which outperforms other state-of-the-art methods. (Link to Publication Site) ● Publication site (DOI): 10.1587/transinf.2018EDP7268 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85071994649 (DOI: 10.1587/transinf.2018EDP7268, Elsevier: Scopus)
73.	Fuji Ren, WenJie Liu and Guoqing Wu : Feature Reuse Residual Networks for Insect Pest Recognition, IEEE Access, Vol.7, 122758-122768, 2019. (Summary) Insect pests are one of the main threats to the commercially important crops. An effective insect pest recognition method can avoid economic losses. In this paper, we proposed a new and simple structure based on the original residual block and named as feature reuse residual block which combines feature from the input signal of a residual block with the residual signal. In each feature reuse residual block, it enhances the capacity of representation by learning half and reuse half feature. By stacking the feature reuse residual block, we obtained the feature reuse residual network (FR-ResNet) and evaluated the performance on IP102 benchmark dataset. The experimental results showed that FR-ResNet can achieve significant performance improvement in terms of insect pest classification. Moreover, to demonstrate the adaptive of our approach, we applied it to various kinds of residual networks, including ResNet, Pre-ResNet, and WRN, and we tested the performance on a series of benchmark datasets: CIFAR-10, CIFAR-100, and SVHN. The experimental results showed that the performance can be improved obviously than original networks. Based on these experiments on CIFAR-10, CIFAR-100, SVHN, and IP102 benchmark datasets, it demonstrates the effectiveness of our approach. (Tokushima University Institutional Repository) ● Metadata: 115145 (Link to Publication Site) ● Publication site (DOI): 10.1109/ACCESS.2019.2938194 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/ACCESS.2019.2938194 (Tokushima University Institutional Repository: 115145, DOI: 10.1109/ACCESS.2019.2938194)
74.	MIN HU, CHUNJIAN YANG, YAQIN ZHENG, XIAOHUA WANG, LEI HE and Fuji Ren : Facial Expression Recognition Based on Fusion Features of Center-Symmetric Local Signal Magnitude Pattern, IEEE Access, Vol.7, No.1, 118435-118445, 2019. (Summary) Local feature descriptors play a fundamental and important role in facial expression recognition. This paper presents a new descriptor, Center-Symmetric Local Signal Magnitude Pattern (CS-LSMP), which is used for extracting texture features from facial images. CS-LSMP operator takes signal and magnitude information of local regions into account compared to conventional LBP-based operators. Additionally, due to the limitation of single feature extraction method and in order to make full advantagesofdifferentfeatures,thispaperemploysCS-LSMPoperatortoextractfeaturesfromOrientational Magnitude Feature Maps (OMFMs), Positive-and-Negative Magnitude Feature Maps (PNMFMs), Gabor FeatureMaps(GFMs)andfacialpatches(eyebrows-eyes,mouths)forobtainingfusedfeatures.UnlikeHOG, which only retains horizontal and vertical magnitudes, our work generates Orientational Magnitude Feature Maps (OMFMs) by expanding multi-orientations. This paper build two distinct feature maps by dividing local magnitudes into two groups, i.e., positive and negative magnitude feature maps. The generated Gabor FeatureMaps(GFMs)arealsogroupedtoreducethecomputationalcomplexity.ExperimentsontheJAFFE andCK+facialexpressiondatasetsshowedthattheproposedframeworkachievedsigni cantimprovement and outperformed some state-of-the-art methods. (Tokushima University Institutional Repository) ● Metadata: 116334 (Link to Publication Site) ● Publication site (DOI): 10.1109/ACCESS.2019.2936976 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/ACCESS.2019.2936976 (Tokushima University Institutional Repository: 116334, DOI: 10.1109/ACCESS.2019.2936976)
75.	MIN HU, YAQIN ZHANG, CHUNJIAN YANG, XIAOHUA WANG, LEI HE, Fuji Ren and XIAOYIN XU : Facial Expression Recognition Using Fusion Features Based on Center-Symmetric Local Octonary Pattern, IEEE Access, Vol.7, No.1, 29882-29890, 2019. (Summary) A local feature descriptor has gained a lot of interest in many applications, such as image retrieval, texture classi cation, and face recognition. This paper proposes a novel local feature descriptor: center-symmetric local octonary pattern (CS-LOP) for facial expression recognition. A CS-LOP operator not only considers the difference of the gray value between central pixels and neighboring pixels in all eight directions but also compares the gray value of four pairs of center-symmetric pixels. Besides, this paper used the CS-LOP to extract diverse features from the preprocessed facial image, the feature map of gradient magnitude, and the feature map of Gabor, and also to make extracted features more abundant and detailed. To evaluate the performance of the proposed method, experiments on JAFFE and CK facial expression datasets demonstrate that the proposed method outperforms the method using the individual descriptor. Compared with other state-of-the-art methods, our approach improves the overall recognition accuracy. (Link to Publication Site) ● Publication site (DOI): 10.1109/ACCESS.2019.2899024 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/ACCESS.2019.2899024 (DOI: 10.1109/ACCESS.2019.2899024)
76.	Yu Gu, Xiang Zhang, Zhi Liu and Fuji Ren : BeSense: Leveraging WiFi Channel Data and Computational Intelligence for Behavior Analysis, IEEE Computational Intelligence Magazine, Vol.14, No.4, 31-41, 2019. (Summary) The ever-evolving informatics technology has gradually bounded human and computer in a compact way. Understanding user behavior becomes a key enabler in many fields such as sedentary-related healthcare, human-computer interaction and affective computing. Traditional sensor-based and vision-based user behavior analysis approaches are obtrusive in general, hindering their usage in real-world. Therefore, in this article, we first introduce the WiFi signal as a new source instead of sensor and vision for unobtrusive user behaviors analysis. Then we design BeSense, a contactless behavior analysis system leveraging signal processing and computational intelligence over WiFi channel state information. We prototype BeSense on commodity low-cost WiFi devices and evaluate its performance in real-world environments. Experimental results have verified its effectiveness in recognizing user behaviors. (Link to Publication Site) ● Publication site (DOI): 10.1109/MCI.2019.2937610 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85073803029 (DOI: 10.1109/MCI.2019.2937610, Elsevier: Scopus)
77.	JUAN LIU, ZHONG HUANG, Fuji Ren and LEI HUA : Drug-Drug Interaction Extraction Based on Transfer Weight Matrix and Memory Network, IEEE Access, Vol.7, No.1, 101260-101268, 2019. (Summary) Extracting drug drug interaction (DDI) in the text is the process of identifying how two target drugs in a given sentence interact. Previous methods, which were limited to conventional machine learning techniques, we are susceptible to issues such as ``vocabulary gap'' and unattainable automation processes in feature extraction. Inspired by deep learning in natural language preprocessing, we addressed theaforementionedproblemsbasedondynamictransfermatrixandmemorynetworks.ATM-RNNmethod is proposed by adding the transfer weight matrix in multilayer bidirectional LSTM to improve robustness andintroduceamemorynetworkforfeaturefusion.WeevaluatedtheTM-RNNmodelontheDDIExtraction 2013Task.TheproposedmodelachievedanoverallF-scoreof72.43,whichoutperformsthelatestmethods based on support vector machine and other neural networks. Meanwhile, the experimental results also indicated that the proposed model is more stable and less affected by negative samples. (Keyword) Drug drug interaction extraction / memory network / multilayer bidirectional LSTM (Tokushima University Institutional Repository) ● Metadata: 116333 (Link to Publication Site) ● Publication site (DOI): 10.1109/ACCESS.2019.2930641 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/ACCESS.2019.2930641 (Tokushima University Institutional Repository: 116333, DOI: 10.1109/ACCESS.2019.2930641)
78.	Tian Chen, Yongsheng Zuo, Xin An and Fuji Ren : Test data compatible compression method based on tri-state signal, Journal of Computer Applications, Vol.39, No.6, 1863-1868, 2019. (Link to Publication Site) ● Publication site (DOI): 10.11772/j.issn.1001-9081.2018112334 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.11772/j.issn.1001-9081.2018112334 (DOI: 10.11772/j.issn.1001-9081.2018112334)
79.	Xiaohua Wang, Muzi Peng, Lijuan Pan, Min Hu, Chunhua Jin and Fuji Ren : Two-level attention with two-stage multi-task learning for facial emotion recognition, Journal of Visual Communication and Image Representation, Vol.62, No.1, 217-225, 2019. (Summary) Compared with facial emotion recognition on categorical model, the dimensional emotion recognition can describe numerous emotions of the real world more accurately. Most prior works of dimensional emotion estimation only considered laboratory data and used video, speech or other multi-modal features. The effect of these methods applied on static images in the real world is unknown. In this paper, a two-level attention with two-stage multi-task learning (2Att-2Mt) framework is proposed for facial emotion estimation on only static images. Firstly, the features of corresponding region(position-level features) are extracted and enhanced automatically by first-level attention mechanism. In the following, we utilize Bi-directional Recurrent Neural Network(Bi-RNN) with self-attention(second-level attention) to make full use of the relationship features of different layers(layer-level features) adaptively. Owing to the inherent complexity of dimensional emotion recognition, we propose a two-stage multi-task learning structure to exploited categorical representations to ameliorate the dimensional representations and estimate valence and arousal simultaneously in view of the correlation of the two targets. The quantitative results conducted on AffectNet dataset show significant advancement on Concordance Correlation Coefficient(CCC) and Root Mean Square Error(RMSE), illustrating the superiority of the proposed framework. Besides, extensive comparative experiments have also fully demonstrated the effectiveness of different components. (Link to Publication Site) ● Publication site (DOI): 10.1016/j.jvcir.2019.05.009 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85066409780 (DOI: 10.1016/j.jvcir.2019.05.009, Elsevier: Scopus)
80.	Tian Chen, Zhangang Chen, Xiaohui Yuan, Sihang Ju and Fuji Ren : Emotion Recognition Method Based on Instantaneous Energy of Electroencephalography, Computer Engineering, Vol.45, No.4, 196-204, 2019. (Link to Publication Site) ● Publication site (DOI): 10.19678/j.issn.1000-3428.0050486 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.19678/j.issn.1000-3428.0050486 (DOI: 10.19678/j.issn.1000-3428.0050486)
81.	Xiao Sun, Tao Hong, Changliang Li and Fuji Ren : Hybrid Spatiotemporal Models for Sentiment Classification Via Galvanic Skin Response, Neurocomputing, Vol.358, 385-400, 2019. (Summary) Sentiment plays an important role in cognition, creativity, attention, and decision making in people's daily lives. Researchers have made great progress in sentiment recognition through images and speech. In this paper, a multimodal dataset is proposed for sentiment classi cation (MDSTC 1 ) a multimodal dataset col lected with multimodal channels by customized physiological sensors and manually labelled for human sentiment analysis. MDSTC contains galvanic skin response (GSR), pulse, speech, and facial expression data of 100 volunteers labelled with timeline, emotional self-ratings, and personal information such as age, sex and Big Five personality scores, which were collected while watching video clips to stimulate emotions. Using the MDSTC dataset, the GSR channel with six types of emotion labels is used to perform human sentiment analysis in this paper. The GSR signal is converted into a spectrogram to adopt image related methods and deep learning models. A convolutional neural network, long short-term memory, and self-attention mechanism are adopted and combined, and spatiotemporal hybrid models are pro posed to perform human sentiment analysis. Comparisons are performed between the proposed model and state-of-the-art models in related works. The experimental results show that with the proposed spa tiotemporal hybrid models, better results are obtained with respect to precision, recall, and F1-score. The experimental results also show that with the proposed spatiotemporal hybrid models working with GSR, people's emotional changes can be obtained in real time with high precision. (Link to Publication Site) ● Publication site (DOI): 10.1016/j.neucom.2019.05.061 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1016/j.neucom.2019.05.061 (DOI: 10.1016/j.neucom.2019.05.061)
82.	XIN KANG, Yunong Wu and Fuji Ren : Toward action comprehension for searching: Mining actionable intents in query entities, Journal of the Association for Information Science and Technology, 2019. (Keyword) action mining / actionable knowledge / actionable intent ranking (Tokushima University Institutional Repository) ● Metadata: 118254 (Link to Publication Site) ● Publication site (DOI): 10.1002/asi.24220 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85064660402 (Tokushima University Institutional Repository: 118254, DOI: 10.1002/asi.24220, Elsevier: Scopus)
83.	Xiaoxia Liu, Degen Huang, Zhangzhi Yin and Fuji Ren : Recognition of Collocation Frames from Sentences, IEICE Transactions on Information and Systems, Vol.E102-D, No.3, 620-627, 2019. (Summary) Collocation is a ubiquitous phenomenon in languages and accurate collocation recognition and extraction is of great signi cance to many natural language processing tasks. Collocations can be di erentiated from simple bigram collocations to collocation frames(referring to distant multi-gram collocations). So far little focus is put on collocation frames. Oriented to translation and parsing, this study aims to recognize and extract the longest possible collocation frames from given sentences. We rst extract bigram collocations with distributional semantics based method by introducing collocation patterns and integrating some state-of-the-art association measures. Based on bigram collocations extracted by the proposed method, we get the longest collocation frames according to recursive nature and linguistic rules of collocations. Compared with the baseline systems, the proposed method performs signi cantly better in bigram collocation extraction both inprecision and recall. And in extracting collocation frames, the proposed method performs even better with the precision similar to its bigram collocation extraction results. (Link to Publication Site) ● Publication site (DOI): 10.1587/transinf.2018EDP7255 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85063994044 (DOI: 10.1587/transinf.2018EDP7255, Elsevier: Scopus)
84.	XINHUA CAO, TAIHAO Li, HONGLI LI, SHUNREN XIA, Fuji Ren, YE SUN and XIAOYIN XU : A Robust Parameter-Free Thresholding Method for Image Segmentation, IEEE Access, Vol.7, No.1, 3448-3458, 2019. (Summary) Inthispaper,wepresentedanewparameter-freethresholdingmethodforimagesegmentation. In separating an image into two classes, the method employs an objective function that not only maximizes the between-class variance but also the distance between the mean of each class and the global mean of the image. The design of the objective function aims to circumvent the challenge that many existing techniques encounter when the underlying two classes have very different sizes or variances. The advantages of the new method are twofold. First, it is parameter-free, meaning that it can generate consistent results. Second, the new method has a simple form that makes it easy to adapt to different applications. We tested and compared the new method with the standard Otsu method, the maximum entropy method, and the 2D Otsu method on the simulated and real biomedical and photographic images and found that the new method can achieve a more accurate and robust performance. (Keyword) Segmentation / parameter-free thresholding / objective function / histogram (Link to Publication Site) ● Publication site (DOI): 10.1109/ACCESS.2018.2889013 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/ACCESS.2018.2889013 (DOI: 10.1109/ACCESS.2018.2889013)
85.	Kazuyuki Matsumoto, Fuji Ren, Masaya Matsuoka, Minoru Yoshida and Kenji Kita : Slang Feature Extraction by Analyzing Topic Change on Social Media, CAAI Transactions on Intelligence Technology, 2019. (Summary) Recently, we often see words such as youth slang, neologism and Internet slang on social networking sites (SNSs) that are not registered on dictionaries. Because the documents posted to SNSs include a lot of fresh information, they are thought to be useful for collecting information. It is important to analyze these words (hereinafter referred to as slang) and capture their features for the improvement of the accuracy of automatic information collection. This paper aims to analyze what features can be observed in slang by focusing on the topic. We construct topic models from document groups including target slang on Twitter by Latent Dirichlet Allocation (LDA). With the models, we chronologically analyze change of topics during a certain period of time to find out the difference in the features between slang and general words. Then, we propose a slang classification method based on the change of features. (Keyword) Slang / Topic analysis / Latent Dirichlet Allocation / Social media, / Tweet representation (Tokushima University Institutional Repository) ● Metadata: 113246 (Link to Publication Site) ● Publication site (DOI): 10.1049/trit.2018.1060 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1049/trit.2018.1060 (Tokushima University Institutional Repository: 113246, DOI: 10.1049/trit.2018.1060)
86.	Fuji Ren and Jiawen Deng : Background Knowledge Based Multi-Stream Neural Network for Text Classification, Applied Sciences, No.1, 1-18, 2018. (Summary) As a foundation and typical task in natural language processing, text classification has been widely applied in many fields. However, as the basis of text classification, most existing corpus are imbalanced and often result in the classifier tending its performance to those categories with more texts. In this paper, we propose a background knowledge based multi-stream neural network to make up for the imbalance or insufficient information caused by the limitations of training corpus. The multi-stream network mainly consists of the basal stream, which retains original sequence information, and background knowledge-based streams. Background knowledge is composed of keywords and co-occurred words which are extracted from external corpus. Background knowledge-based streams are devoted to realizing supplemental information and reinforce the basal stream. To better fuse the features extracted from different streams, early-fusion and two after-fusion strategies are employed. According to the results obtained from both Chinese corpus and English corpus, it is demonstrated that the proposed background knowledge based multi-stream neural network performs well in classification tasks. (Keyword) classi cation algorithms / knowledge engineering / neural networks / machine learning (Tokushima University Institutional Repository) ● Metadata: 114992 (Link to Publication Site) ● Publication site (DOI): 10.3390/app8122472 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85057618154 (Tokushima University Institutional Repository: 114992, DOI: 10.3390/app8122472, Elsevier: Scopus)
87.	Zhao Han, Fuji Ren and Duoqian Miao : Sentiment Analysis Method Based on an Improved Modifying-MatrixLanguage Model, IEEJ Transactions on Electrical and Electronic Engineering (TEEE), Vol.13, No.10, 1446-1453, 2018. (Summary) In this paper, a sentence-level sentiment analysis method is proposed to deal with sentiment measurement and classificationproblems. It is developed from a model called the synthetic and computational language model (SCLM), which representsmodifying and modified information, respectively, using matrices and vectors. In the proposed method, a global modifyingmatrix of a sentence is constructed, the determinant value of this matrix is calculated and adjusted, and then the final valueis used as the sentiment value of the sentence. Regression experiment shows that the deviation between the output sentimentand the target sentiment does not exceed a class distance of five classes. The classification experiment shows that the proposedmethod has improved most of the performance compared to the simplified SCLM and in some cases, such as in `very positive'class and `very negative' class, reaches higher precision performance than the baseline method. (Keyword) affective computing / sentiment analysis / emotion classification / language model / neural network (Link to Publication Site) ● Publication site (DOI): 10.1002/tee.22711 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1002/tee.22711 (DOI: 10.1002/tee.22711)
88.	Tian Chen, Sihang Ju, Xiaohui Yuan, Mohamed Elhoseny, Fuji Ren and Mingyan Fan : Emotion recognition using empirical mode decomposition and approximation entropy, Computers & Electrical Engineering, Vol.72, No.1, 383-392, 2018. (Summary) Automatic human emotion recognition is a key technology for human-machine interac tion. In this paper, we propose an electroencephalogram (EEG) feature extraction method that leverages empirical mode decomposition and Approximation Entropy. In our proposed method, Empirical Mode Decomposition (EMD) is used to process EEG signals after data processing and obtains several intrinsic eigenmode functions. The Approximation Entropy (ApEn) of the rst four Intrinsic Mode Functions (IMFs) is computed, which is used as the features from EEG signals for learning and recognition. An integration of Deep Belief Net work and Support Vector Machine is devised for classi cation, which takes the eigenvec tors from the extracted feature to identify four principal human emotions, namely happy, calm, sad, and fear. Experiments are conducted with EEG data acquired with a 16-lead device. Our experimental results demonstrate that the proposed method achieves an im proved accuracy that is highly competitive to the state-of-the-art methods. The average accuracy is 83.34%, and the best accuracy reaches 87.32% (Link to Publication Site) ● Publication site (DOI): 10.1016/j.compeleceng.2018.09.022 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1016/j.compeleceng.2018.09.022 (DOI: 10.1016/j.compeleceng.2018.09.022)
89.	Fuji Ren, Yindong Dong and Wei Wang : Emotion recognition based on physiological signals using brain asymmetry index and echo state network, Neural Computing & Applications, 2018. (Summary) This paper proposes a method to evaluate the degree of emotion being motivated in continuous music videos based on asymmetry index (AsI). By collecting two groups of electroencephalogram (EEG) signals from 6 channels (Fp1, Fp2, Fz and AF3, AF4, Fz) in the left and right hemispheres, multidimensional directed information is used to measure the mutual information shared between two frontal lobes, and then, we get AsI to estimate the degree of emotional induction. In order to evaluate the effect of AsI processing on physiological emotion recognition, 32-channel EEG signals, 2-channel EEG signals and 2-channel EMG signals are selected for each subject from the DEAP dataset, and different sub-bands are extracted using wavelet packet transform. k-means algorithm is used to cluster the wavelet packet coef cients of each subband, and the probability distribution of the coef cients under each cluster is calculated. Finally, the probability distribution value of each sample is sent as the original features into echo state network for unsupervised intrinsic plasticity training; the reservoir state nodes are selected as the nal feature vector and fed into the support vector machine. The experimental results show that the proposed algorithm can achieve an average recognition rate of 70.5% when the subjects are independent. Compared with the case without AsI, the recognition rate is increased by 8.73%. On the other hand, the ESN is adopted for the original physiological feature re nement which can signi cantly reduce feature dimensions and be more bene cial to the emotion classi cation. Therefore, this study can effectively improve the performance of human machine interface systems based on emotion recognition. (Link to Publication Site) ● Publication site (DOI): 10.1007/s00521-018-3664-1 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1007/s00521-018-3664-1 (DOI: 10.1007/s00521-018-3664-1)
90.	Xiaohua Wang, Ying Chen, Min Hu and Fuji Ren : Occluded Facial Expression Recognition Based on Asymmetric Region Weber Local Descriptor and Block Similarity Weighting, Laser & Optoelectronics Progress, Vol.55, No.4, 1-8, 2018. (Link to Publication Site) ● Publication site (DOI): 10.3788/LOP55.041013 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85057086150 (DOI: 10.3788/LOP55.041013, Elsevier: Scopus)
91.	Min Hu, Keke Zhang, Xiaohua Wang and Fuji Ren : Video facial expression recognition combined with sliding window dynamic time warping and CNN, Journal of Image and Graphics, Vol.23, No.8, 1143-1153, 2018.
92.	Li Quan, Zhiliang Wang and Fuji Ren : A Novel Two-Layered Reinforcement Learning for Task Of oading with Tradeoff between Physical Machine Utilization Rate and Delay, Future Internet, Vol.60, No.10, 1-17, 2018. (Summary) Mobile devices could augment their ability via cloud resources in mobile cloud computing environments. This paper developed a novel two-layered reinforcement learning (TLRL) algorithm toconsider taskof oading forresource-constrained mobiledevices. Asopposed toexisting literature, the utilization rate of the physical machine and the delay for of oaded tasks are taken into account simultaneously by introducing a weighted reward. The high dimensionality of the state space and action space might affect the speed of convergence. Therefore, a novel reinforcement learning algorithm with a two-layered structure is presented to address this problem. First, k clusters of the physical machines are generated based on the k-nearest neighbors algorithm (k-NN). The rst layer of TLRL is implemented by a deep reinforcement learning to determine the cluster to be assigned for the of oaded tasks. On this basis, the second layer intends to further specify a physical machine for task execution. Finally, simulation examples are carried out to verify that the proposed TLRL algorithm is able to speed up the optimal policy learning and can deal with the tradeoff between physical machine utilization rate and delay. (Tokushima University Institutional Repository) ● Metadata: 117740 (Link to Publication Site) ● Publication site (DOI): 10.3390/fi10070060 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.3390/fi10070060 (Tokushima University Institutional Repository: 117740, DOI: 10.3390/fi10070060)
93.	Mingxing Jiang, Min Hu, Xiaohua Wang, Fuji Ren and Haowen Wang : Dual-Modal Emotion Recognition Based on Facial Expression and Body Posture in Video Sequences, Laser & Optoelectronics Progress, Vol.55, 161-168, 2018. (Link to Publication Site) ● Publication site (DOI): 10.3788/LOP55.071004 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85050638107 (DOI: 10.3788/LOP55.071004, Elsevier: Scopus)
94.	Zhao Han, Duoqian Miao and Fuji Ren : Rough Set Based Knowledge Predicate Analysis of Chinese Knowledge Based Question Answering, COMPUTER SCIENCE, Vol.45, No.6, 183-186, 2018. (Summary) In knowledge based question answering system, the performance of knowledge predicate analysis can affect the overall match result of knowledge triple The knowledge predicate analysis of Chinese short questionis difficult because of the uncertainty of Chinese knowledge predicate representation Based on the rough set theory, a new definition of knowledge predicate analysis of knowledge based questions answering was given, and a new method was proposed to analyze the knowledge predicate of question It can reduce the words which are weakly related with the knowledge predicate, and then the words which are more related with knowledge predicate representation will be used to match the knowledge triples to improve the overall performance of system The experiment results verify the validity of the method (Link to Publication Site) ● Publication site (DOI): 10.11896/j.issn.1002-137X.2018.06.032 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.11896/j.issn.1002-137X.2018.06.032 (DOI: 10.11896/j.issn.1002-137X.2018.06.032)
95.	Tian Chen, Jiawei Wang, Xin An and Fuji Ren : Parallel test scheduling optimization method for three-dimensional chip with multi-core and multi-layer, Journal of Computer Applications, Vol.38, No.6, 1795-1800, 2018. (Summary) In order to solve the problem of high cost of chip testing in the process of Three-Dimensional ( 3D) chip manufacturing a new scheduling method based on Time Division Multiplexing ( TDM) was proposed to optimize the testing resources between layers layer and core cooperatively Firstly the shift registers were arranged on each layer of 3D chip and the testing frequency was divided properly between the layers and cores of the same layer under the control of shift register group on input data so that the cores in different locations could be tested in parallel Secondly greedy algorithm was used to optimize the allocation of registers for reducing the free test cycles of core parallel test Finally Discrete Binary Particle Swarm Optimization ( DBPSO) algorithm was used to find out the best 3D stack layout so that the transmission potential of the Through Silicon Via ( TSV) could be adequately used to improve the parallel testing efficiency and reduce the testing time The experimental results show that under the power constraints the utilization rate of the optimized whole Test Access Mechanism ( TAM) is increased by an average of 16 28% and the testing time of the optimized 3D stack is reduced by an average of 13 98% The proposed method can decrease the time and reduce the cost of testing (Link to Publication Site) ● Publication site (DOI): 10.11772/j.issn.1001-9081.2017123002 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.11772/j.issn.1001-9081.2017123002 (DOI: 10.11772/j.issn.1001-9081.2017123002)
96.	Kazuyuki Matsumoto, Kyosuke Akita, Fuji Ren, Minoru Yoshida and Kenji Kita : Intimacy Estimation of the Characters in Drama Scenario, Journal of Japan Society for Fuzzy Theory and Intelligent Informatics, Vol.30, No.3, 591-604, 2018. (Summary) Recently, a portable digital device equipped with voice guidance has been widely used, increasing the demand for the usabilityconscious dialogue system. One of the problems with the existing dialogue system is its immature application to non-task-orienteddialogue. Non-task-oriented dialogue requires some scheme that enables smooth and flexible conversations with a user. For example,it would be possible to provide topics related to a person who is familiar with a user or avoid providing topics related to a personwho is not a good friend with the user, by considering relationship with others in real life of the user. In this paper, we focus on thedialogue made by the two characters in a drama scenario, and tried to express their relationship with a scale of intimacy degree.There will be such various elements related to the intimacy degree as the frequency of response to the utterance and the attitude ofa speaker during the dialogue. We focus on the emotional state of the speaker during the utterance and try to realize an intimacyestimation with high accuracy. As the evaluation result, we achieved high accuracy in intimacy estimation than the existing methodbased on speech role. (Keyword) intimacy degree / scenario dialogue / emotional state (Tokushima University Institutional Repository) ● Metadata: 113247 (Link to Publication Site) ● Publication site (DOI): 10.3156/jsoft.30.3_591 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1390564237991620096 ● Search Scopus @ Elsevier (DOI): 10.3156/jsoft.30.3_591 (Tokushima University Institutional Repository: 113247, DOI: 10.3156/jsoft.30.3_591, CiNii: 1390564237991620096)
97.	Zhao Han, Duoqian Miao, Fuji Ren and Hongyun Zhang : Rough Set Knowledge Discovery Based Open Domain Chinese Question Answering Retrieval, Journal of Computer Research and Development, Vol.55, No.5, 958-967, 2018. (Link to Publication Site) ● Publication site (DOI): 10.7544/issn1000-1239.2018.20170232 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85053434589 (DOI: 10.7544/issn1000-1239.2018.20170232, Elsevier: Scopus)
98.	Liangfeng Xu, Yonghai Liu, Min Hu, Xiaohua Wang and Fuji Ren : Speech emotion recognition based on improved complete local binary pattern of spectrogram images, Journal of Electronic Measurement and Instrument, Vol.32, No.5, 25-32, 2018. (Summary) A novel speech emotion recognition is proposed in the paper in whichthe improved complete local binary pattern and the power exponential class weighted fusion are used Firstly the original speech sample is transformedinto a spectrum diagram then the 5scale 8-directional Log-Gabor filter is used to deal with the language spectrum in order to enlarge the detail information of the image Then the block histogram features of the uniform complete local binary pattern sign feature and improved complete local binary patternmagnitude feature are extracted and cascaded as a new fusion feature called improved complete local binary patternsign magnitude Finally based on support vector machine these three features are weighted by the decision level in order to achieve the speech emotion recognition The experiment results indicate that theimproved complete local binary patternmagnitude feature and the fusion feature can reduce the feature dimension and improve the effect of system identification The exponential weighted fusion method expands the gap between classifiers and gives a larger weight to the classifier with better classification performance which can finally enhance the performance of speech emotion recognition effectively Compared with other algorithms the experiment results also show the effectiveness of the proposed algorithm (Link to Publication Site) ● Publication site (DOI): 10.13382/j.jemi.2018.05.004 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.13382/j.jemi.2018.05.004 (DOI: 10.13382/j.jemi.2018.05.004)
99.	Fuji Ren and Ning Liu : Emotion computing using Word Mover's Distance features based on Ren_CECps, PLoS ONE, Vol.13, No.4, 1-17, 2018. (Summary) In this paper, we propose an emotion separated method(SeTF·IDF) to assign the emotion labels of sentences with different values, which has a better visual effect compared with the values represented by TF·IDF in the visualization of a multi-label Chinese emotional corpus Ren_CECps. Inspired by the enormous improvement of the visualization map propelled by the changed distances among the sentences, we being the first group utilizes the Word Mover's Distance(WMD) algorithm as a way of feature representation in Chinese text emotion classification. Our experiments show that both in 80% for training, 20% for testing and 50% for training, 50% for testing experiments of Ren_CECps, WMD features get the best f1 scores and have a greater increase compared with the same dimension feature vectors obtained by dimension reduction TF·IDF method. Compared experiments in English corpus also show the efficiency of WMD features in the cross-language field. (Keyword) Algorithms / Artificial Intelligence / Computer Simulation / Emotions / Humans / Models, Theoretical (Tokushima University Institutional Repository) ● Metadata: 112367 (Link to Publication Site) ● Publication site (DOI): 10.1371/journal.pone.0194136 (Link to Search Site for Scientific Articles) ● PubMed @ National Institutes of Health, US National Library of Medicine (PMID): 29624573 ● Search Scopus @ Elsevier (PMID): 29624573 ● Search Scopus @ Elsevier (DOI): 10.1371/journal.pone.0194136 (Tokushima University Institutional Repository: 112367, DOI: 10.1371/journal.pone.0194136, PubMed: 29624573)
100.	Xiao Sun, Chen Zhang and Fuji Ren : User Emotion Modeling and Anomaly Detection Based on Social Media, Journal oc Chinese Information Processing, Vol.32, No.4, 120-129, 2018. (Summary) For abnormal emotional detection among micro-blog users, this paper proposes ananomaly detection method based on the joint probability density of multivariate Gaussian model and power-law distribution. In the xperiments, the anomaly detection accuracy is 83. 49% in terms of individual user, and 87. 84% in terms of month. Statistics reveals that individual users' neutral, happy and sad emotions fall into the normal distribution, but the amazed and angry emotions are not. Emotions of micro-blogs released by groups confirm to the power law distribution, but not those by the individual.
101.	Yiming Tang, Gangyong Feng, Fuji Ren, Xianghui Hu and Youcheng Zhang : Fuzzy clustering validity index facing data set with complexity structure, Journal of Electronic Measurement and Instrument, Vol.32, No.4, 119-127, 2018. (Summary) How to effectively determine the clustering number is one of the historical challenges in the clustering field A typical algorithm for clustering is the fuzzy c-means algorithm Nowadays it is difficult for clustering validity index to make accurate judgment for complex data structure and the huge disparity of cluster size Aiming at the problem a new clustering validity index VGSDC( index for geometry structure and different clusters) is proposed for the geometry structure of data set and clusters with different size The compactness strategy is obtained by square error sum within the classes as well as weights of membership degree and then the separation computing method is gotten by minimum distance between cluster centers together with distance sum from centers to average center And finally the new validity index VGSDC is obtained Furthermore the best clustering number can be automatically obtained by the number of categories corresponding to the extreme value of VGSDC Through the experiment in 6 data structure it is found that the proposed VGSDC gets the better performance comparing with 11 kinds of clustering validity indexes VGSDC can not only handle multiple types of data sets and also provide full consideration to the structure characteristics and complexity of the data sets As a result it can be applied to large data sets with huge differences of clustering center distance (Link to Publication Site) ● Publication site (DOI): 10.13382/j.jemi.2018.04.017 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.13382/j.jemi.2018.04.017 (DOI: 10.13382/j.jemi.2018.04.017)
102.	Yiming Tang, Youcheng Zhang, Fuji Ren, Xianghua Hu, Xiaocheng Song and Gangyong Feng : FMT symmetric I* method of fuzzy reasoning, Journal of Nanjing University (Natural Science), Vol.54, No.4, 706-713, 2018.
103.	Jun Liu, Chengqiang Zhu, Xi Wu, Wei Wang and Fuji Ren : Yield Optimization Technique for Three Dimensional Memory Based on Redundancy Sharing Among Adjacent Layers, ACTA Electronica Sinica, Vol.46, No.3, 629-635, 2018. (Link to Publication Site) ● Publication site (DOI): 10.3969/j.issn.0372-2112.2018.03.017 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85052302364 (DOI: 10.3969/j.issn.0372-2112.2018.03.017, Elsevier: Scopus)
104.	Jing Zhang, Degen Huang, Kaiyu Huang, Zhuang Liu and Fuji Ren : Corpus Expansion for Neural CWS on Microblog-Oriented Data with λ-Active Learning Approach, IEICE Transactions on Information and Systems, Vol.E101-D, No.3, 778-785, 2018. (Summary) Microblog data contains rich information of real-world events with great commercial values, so microblog-oriented natural language processing (NLP) tasks have grabbed considerable attention of researchers. However, the performance of microblog-oriented Chinese Word Segmentation (CWS) based on deep neural networks (DNNs) is still not satisfying. One critical reason is that the existing microblog-oriented training corpus is inadequate to train e ective weight matrices for DNNs. In this paper, we propose a novel active learning method to extend the scale of the training corpus for DNNs. However, due to a large amount of partiallyoverlappedsentencesinthemicroblogs,itisdi culttoselectsamples with high annotation values from raw microblogs during the active learning procedure. To select samples with higher annotation values, parameter λ is introduced to control the number of repeatedly selected samples. Meanwhile, various strategies are adopted to measure the overall annotation values of a sample during the active learning procedure. Experiments on the benchmark datasets of NLPCC 2015 show that our λ-active learning method outperforms the baseline system and the state-of-the-art method. Besides, the results also demonstrate that the performances of the DNNs trained on the extended corpus are signi cantly improved. (Link to Publication Site) ● Publication site (DOI): 10.1587/transinf.2017EDP7239 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1587/transinf.2017EDP7239 (DOI: 10.1587/transinf.2017EDP7239)
105.	Xiaohua Wang, Chen Xia, Min Hu and Fuji Ren : Facial Expression Recognition Based on the Fusion of Spatio-temporal Features in Video Sequences, Journal of Electronics and Information Technology, Vol.40, No.3, 626-632, 2018. (Summary) For facial expression recognition based on video sequences, the changing information of facial regions along the time axis can be described by dynamic descriptors more effectively than static descriptors. This paper proposes an expression recognition method based on the dynamic texture and motion information, learning from the principle of Local Binary Pattern on Three Orthogonal Planes (LBP-TOP), Spatio-Temporal Weber Local Descriptor (STWLD) is proposed to describe the dynamic texture feature information of the facial expression sequence. Moreover, using Block-based Histogram of Optical Flow features (BHOF), the motion information can be described. Through the combination of the dynamic texture and motion information, and finally SVM is applied to complete the expression classification. The results of the cross experiments on the CK + and MMI expression database show that the method achieves better performance than methods using the single descriptors. The comparison experiments with other related methods also prove the superiority of the method. (Link to Publication Site) ● Publication site (DOI): 10.11999/JEIT170592 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85047991227 (DOI: 10.11999/JEIT170592, Elsevier: Scopus)
106.	Xiao Sun, Chen Zhang, Guoqiang Li, Daniel Sun, Fuji Ren, Albert Zomaya and Rajiv Ranjan : Detecting Users' Anomalous Emotion Using Social Media for Business Intelligence, Journal of Computational Science, Vol.25, 193-200, 2018. (Summary) Anomaly detection in sentiment analysis refers to detecting users' abnormal opinions, sentiment patterns or special temporal aspects of such patterns. Users' emotional state extracted from social media contains business information and business value for decision making. Social media platforms, such as Sina Weibo or Twitter, provide a vast source of information, which include user feedbacks, opinions and information on most issues. Many organizations also leverage social media platforms to publish information about events, products, services, policies and other topics frequently, analyzing social media data to identify abnormal events and make decisions in a timely manner is a beneficial topic. This paper adopts the multivariate Gauss distribution with the power-law distribution to model and analyze the users' emotion of micro-blogs and detect abnormal emotion state. With the measure of joint probability density value and the validation of the corpus, anomaly detection accuracy of individual user is 83.49% and of different month is 87.84% by this method. Through the distribution test, the results show that individual users' neutral, happy and sad emotions obey the normal distribution, but the surprised and angry emotions do not. Besides, emotions of micro-blogs released by groups obey power-law distribution, but the individual emotions do not. This paper proposes a quantitative method for abnormal emotion detection on social media, which automatically captures the correlation between different features of the emotions, and saves a certain amount of time by batch calculation of the joint probability density of data sets. The method can help the businesses and government organizations to make decisions according to the user's affective disposition, intervene early or adopt proper strategies if needed. (Keyword) Business intelligence / Sentiment analysis / Anomaly detection / Multivariate Gaussian distribution / Decision making (Link to Publication Site) ● Publication site (DOI): 10.1016/j.jocs.2017.05.029 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1016/j.jocs.2017.05.029 (DOI: 10.1016/j.jocs.2017.05.029)
107.	Fuji Ren : About unclear power of artificial intelligence, Communication of Chinese Association for Artificial Inteigence, Vol.8, No.1, 6-9, 2018. (Summary) この招待論文において，ビッグデータ・クラウド・深層学習による駆使した人工知能の現状・問題・将来展望を述べた．特に，人工知能の具体的なパワーについて論じた．さらに，人工知能の三つレベルにおける計算知能・感知知能・認知知能について，著者の観点を述べて，このからの人工知能は，理解をメインの挑戦として，推進しなければならない．
108.	XIN KANG, Fuji Ren and Yunong Wu : Exploring latent semantic information for textual emotion recognition in Blog articles, IEEE/CAA Journal of Automatica Sinica, Vol.5, No.1, 204-216, 2018. (Keyword) emotion recognition / natural language understanding / emotion-topic model / Bayesian inference / multi-label classification (Tokushima University Institutional Repository) ● Metadata: 115378 (Link to Publication Site) ● Publication site (DOI): 10.1109/JAS.2017.7510421 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/JAS.2017.7510421 (Tokushima University Institutional Repository: 115378, DOI: 10.1109/JAS.2017.7510421)
109.	Taihao Li, Tuya Naren, Jianshe Zhou, Fuji Ren and Shupeng Liu : An Improved K Means Algorithm Based on Initial Clustering Center Optimization, ZTE Communications, Vol.15, No.S2, 43-46, 2017. (Summary) The K means algorithm is widely known for its simplicity and fastness in text clustering. However, the selection of the initial clus tering center with the traditional K means algorithm is some random, and therefore, the fluctuations and instability of the cluster ing results are strongly affected by the initial clustering center. This paper proposed an algorithm to select the initial clustering center to eliminate the uncertainty of central point selection. The experiment results show that the improved K means clustering algorithm is superior to the traditional algorithm. (Link to Publication Site) ● Publication site (DOI): 10.3969/j.issn.1673-5188.2017.S2.007 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.3969/j.issn.1673-5188.2017.S2.007 (DOI: 10.3969/j.issn.1673-5188.2017.S2.007)
110.	Fuji Ren and Kazuyuki Matsumoto : Emotion Analysis on Social Big Data, ZTE Communications, Vol.15, No.S2, 30-37, 2017. (Summary) In this paper, we describe a method of emotion analysis on social big data. Social big data means text data that is emerging on In ternet social networking services.We collect multilingual web corpora and annotated emotion tags to these corpora for the purpose of emotion analysis. Because these data are constructed by manual annotation, their quality is high but their quantity is low. If we create an emotion analysis model based on this corpus with high quality and use the model for the analysis of social big data, we might be able to statistically analyze emotional sensesand behavior of the people in Internet communications, which we could not know before. In this paper, we create an emotion analysis model that integrate the high quality emotion corpus and the automatic constructed corpus that we created in our past studies, and then analyze a large scale corpus consisting of Twitter tweets based on the model. As the result of time series analysis on the large scale corpus and the result of model evaluation, we show the effective ness of our proposed method. (Link to Publication Site) ● Publication site (DOI): 10.3969/j.issn.1673-5188.2017.S2.005 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.3969/j.issn.1673-5188.2017.S2.005 (DOI: 10.3969/j.issn.1673-5188.2017.S2.005)
111.	Minjia Li, Lun Xie, Zhiliang Wang and Fuji Ren : Emotion and Cognitive Reappraisal Based on GSR Wearable Sensor, ZTE Communications, Vol.15, No.S2, 18-22, 2017. (Summary) Various wearable equipment enables us to measure people behavior by physiological signals. In our research, we present one gal vanic skin reaction (GSR) wearable sensor which can analyze human emotions based on cognition reappraisal. First, We research the factors of emotional state transition in Arousal Valence Stance(AVS) emotional space. Second, the influence of the cognition on emotional state transition is considered, and the reappraisal factor based on Gross regulation theory is established to correct the effectiveness from cognitive reappraisal ability to emotional state transition. Third, based on the previous work, we establish a GSR emotion sensing system for predicting emotional state transition and considering the correlation between GSR signals and emotions. Finally, an overall wearable sensor layout is built. In the experiment part, we invited 30 college students to wear our GSR sensors and watch 14 kinds of affective videos. We recorded their GSR signals while asking them to record their emotional states synchronously. The experiment results show different reappraisal factors can predict subjects'emotional state transition well and indirectly confirm the feasibility of the Gross regulation theory. (Link to Publication Site) ● Publication site (DOI): 10.3969/j.issn.1673-5188.2017.S2.003 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.3969/j.issn.1673-5188.2017.S2.003 (DOI: 10.3969/j.issn.1673-5188.2017.S2.003)
112.	Fuji Ren, Yanqiu Li and Min Hu : Multi-classifier ensemble based on dynamic weights, Multimedia Tools and Applications, Vol.9, No.2, 1-15, 2017. (Summary) In this study, a novel multi-classifier ensemble method based on dynamic weights is proposed to reduce the interference of unreliable decision information and improve the accuracy of fusion decision. The algorithm defines decision credibility to describe the realtime importance of the classifier to the current target, combines this credibility with the reliability calculated by the classifier on the training data set and dynamically assigns the fusion weight to the classifier. Compared with other methods, the contribution of different classifiers to fusion decision in acquiring weights is fully evaluated in consideration of the capability of the classifier to not only identify different sample regions but also output decision information when identifying specific targets. Experimental results on public face databases show that the proposed method can obtain higher classification accuracy than that of single classifier and some popular fusion algorithms. The feasibility and effectiveness of the proposed method are verified. (Keyword) Dynamicweights / Multi-classifier ensemble / Reliability / Decisioncredibility / Face recognition (Tokushima University Institutional Repository) ● Metadata: 115608 (Link to Publication Site) ● Publication site (DOI): 10.1007/s11042-017-5480-5 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1007/s11042-017-5480-5 (Tokushima University Institutional Repository: 115608, DOI: 10.1007/s11042-017-5480-5)
113.	Kazuyuki Matsumoto, Fuji Ren, Minoru Yoshida and Kenji Kita : Review Score Estimation Based on Transfer Learning of Different Media Review Data, International Journal of Advanced Intelligence (IJAI), Vol.9, No.4, 541-555, 2017. (Summary) We propose a model to classify reviews based on review data from different media sources. Recently, research has been actively conducted on transfer learning between different domains with various kinds of big data as the target. The fact that evaluation expressions often vary in different domains presents a barrier to reputation analysis. Users commonly use various linguistic expressions to refer to creative works, depending on the specific media form.For example, the terms or expressions used in anime to describe creative works within that medium are different from the expressions used in comics, or games or movies. These differences can be considered as features of each individual medium. We should expect, then, that there would be differences in evaluation expressions among the various media, as well. We analyze the effects of such differences on classification accuracy by conducting transfer learning between review data from different media and demonstrate compatibility between the original (pre-transfer) and target (post-transfer) media by constructing a review classification model. As a result of our evaluation experiments, we are able to more accurately estimate review scores without using SO-Scores for training review fragments based on Long Short-Term Memory (LSTM) rather than using a method based on SO-Scores. (Keyword) review classification / transfer learning / Long Short-Term Memory / different media (Tokushima University Institutional Repository) ● Metadata: 113252 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1570572702840072192 (Tokushima University Institutional Repository: 113252, CiNii: 1570572702840072192)
114.	Xiao Sun, Man LV, Changqin Quan, Fang Tian, Fuji Ren and Kunxia Wang : Fine-Grained Emotion Elements Extraction and Tendency Judgment Based on Mixed Model, Information Engineering Express, Vol.3, No.4, 21-32, 2017. (Summary) Nowadays, with the development of internet technology and electronic commerce, the Web storages huge number of product reviews comment by customers. Product reviews tend to be more objective in reflecting the real situation of the product, more and more customers post product reviews at merchant websites in order to make an informed choice. However, a large number of reviews made it difficult to track the comments and suggestions that customers made. In this paper, a fine-grained emotional element detection and emotional tendency judgment method based on conditional random fields (CRFs) and support vector machine (SVM) was proposed. This model introduces semantics and word meaning in CRF model to improve the robustness. In SVM model, deep semantic information imported based on neural network to improve the traditional bag of word model. Experimental results show that the proposed model with deep features efficiently improved the F-Measure. (Keyword) 俗語 / トピック分析 / 時系列分析
115.	Yu Gu, Jinhai Zhan, Yusheng Ji, Jie Li, Fuji Ren and Shangbin Gao : MoSense: An RF-Based Motion Detection System via Off-the-Shelf WiFi Devices, IEEE Internet of Things Journal, Vol.4, No.6, 2326-2341, 2017. (Summary) Motion is a critical indicator of human presence and activities. Recent developments in the field of indoor motion detection have revealed their potentials in enhancing our living experiences through applications like intrusion detection and sleep monitoring. However, existing solutions still face several critical downsides such as the availability (specialized hardware), reliability (illumination and line-of-sight constraints), and privacy issues (being watched). To overcome such shortages, a radio frequency (RF) based device-free motion detection system (MoSense) is designed via leveraging the attenuation of ubiquitous WiFi signals induced by motions to deliver a reliable and transparent detection service in realtime. The design and implementation of MoSense face two challenges: 1) characterizing stationary states and 2) the noisy subcarriers. For the first challenge, a silence analysis model is proposed to characterize stationary states for distinguishing motions. For the second challenge, we design a distance-based mechanism to select certain subcarriers that better capture the impact of motions from the noisy channel through measuring the similarity between subcarriers. A prototype of MoSense is realized and evaluated in real environments. By comparing MoSense with other two state-of-the-art systems, i.e., FIMD and FRID, we have shown that MoSense is superior in terms of precision, false negative rate and computational complexity. Considering that MoSense is compatible with existing WiFi infrastructure, it constitutes a low-cost yet promising solution for motion detection. (Link to Publication Site) ● Publication site (DOI): 10.1109/JIOT.2017.2754578 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85030635955 (DOI: 10.1109/JIOT.2017.2754578, Elsevier: Scopus)
116.	Yunong Wu, Kenji Kita, Kazuyuki Matsumoto, XIN KANG and Fuji Ren : Constructing A Short Text Conversation system Based on the Relations Between Posts and Comments, International Journal of Advanced Intelligence (IJAI), Vol.9, No.3, 369-380, 2017.
117.	Xiao Sun, Xiaoqi Peng, Min Hu and Fuji Ren : Extended Multi-modality Features and Deep Learning Based Microblog Short Text Sentiment Analysis, Journal of Electronics and Information Technology, Vol.39, No.9, 2048-2055, 2017. (Summary) This paper presents a Deep Belief Nets (DBN) model and a multi-modality feature extraction method to extend features , dimensionalities of short text for Chinese microblogging sentiment classification. Besides traditional features sets for document classification, comments for certain posts are also extracted as part of the microblogging features according to the relationship between commenters and posters through constructing microblogging social network as input information. Multi-modality features are combined and adopted as the input vector for DBN. A DBN model, which is stacked with several layers of Restricted Boltzmann Machine (RBM), is implemented to initialize the structure of neural network. The RBM layers can take probability distribution samples of input data to learn hidden syntactic structures for better feature representation. A Classification RBM (ClassRBM) layer, which is stacked on top of the former RBM layers, is adapted to achieve the final sentiment classification. The results demonstrate that, with proper structure and parameter, the performance of the proposed deep learning method on sentiment classification is better than the state of the art surface learning models such as SVM or NB, which proves that DBN is suitable for short-length document classification with the proposed feature dimensionality extension method. (Link to Publication Site) ● Publication site (DOI): 10.11999/JEIT160975 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85032935044 (DOI: 10.11999/JEIT160975, Elsevier: Scopus)
118.	Heng Zhang, Shupeng Liu, Xiangfei Yang, Na Chen, Fufei Pang, Zhenyi Chen, Tingyun Wang, Jianshe Zhou, Fuji Ren, Xiaoyin Xu and Taihao Li : LED Phototherapy With Gelatin Sponge Promotes Wound Healing in Mice, Photochemistry and Photobiology, 2017. (Summary) Tiny but highly efficient, a light emitting diode (LED) can power a therapy device, such as a phototherapy device, and, at the same time, decrease the device's size requirements. In this study, a LED phototherapy device was designed to investigate the possible impact on wound healing using a mouse model and a cell line exposed to red and blue light. To enhance wound phototherapy, a gelatin sponge was fabricated. Results showed that the red and blue lights promoted cell growth and wound healing, while the blue light with a gelatin sponge protected the wound from infection in the early stages of wound healing. The LED phototherapy device combined with the gelatin sponge, therefore, has potential significance in clinical application for wound healing. (Keyword) 俗語 / トピック分析 / 時系列分析 (Link to Publication Site) ● Publication site (DOI): 10.1111/php.12816 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1111/php.12816 (DOI: 10.1111/php.12816)
119.	Jun Liu, Jin Li, Wei Wang and Fuji Ren : A Stacking Scheme Using Adjacent Redundancy Across Dies for 3D-stacked Memory, Microelectronics & Computer, Vol.34, No.7, 1-6, 2017. (Keyword) 俗語 / トピック分析 / 時系列分析
120.	Changqin Quan, Bin Zhang, Xiao Sun and Fuji Ren : A combined cepstral distance method for emotional speech recognition, International Journal of Advanced Robotic Systems, Vol.14, No.4, 1-9, 2017. (Summary) Affective computing is not only the direction of reform in artificial intelligence but also exemplification of the advanced intelligent machines. Emotion is the biggest difference between human and machine. If the machine behaves with emotion, then the machine will be accepted by more people. Voice is the most natural and can be easily understood and accepted manner in daily communication. The recognition of emotional voice is an important field of artificial intelligence. However, in recognition of emotions, there often exists the phenomenon that two emotions are particularly vulnerable to confusion. This article presents a combined cepstral distance method in two-group multi-class emotion classification for emotional speech recognition. Cepstral distance combined with speech energy is well used as speech signal endpoint detection in speech recognition. In this work, the use of cepstral distance aims to measure the similarity between frames in emotional signals and in neutral signals. These features are input for directed acyclic graph support vector machine classification. Finally, a two-group classification strategy is adopted to solve confusion in multi-emotion recognition. In the experiments, Chinese mandarin emotion database is used and a large training set (1134 + 378 utterances) ensures a powerful modelling capability for predicting emotion. The experimental results show that cepstral distance increases the recognition rate of emotion sad and can balance the recognition results with eliminating the over fitting. And for the German corpus Berlin emotional speech database, the recognition rate between sad and boring, which are very difficult to distinguish, is up to 95.45%. (Keyword) Cepstral distance / emotional speech recognition / two-group classification / principal component analysis (Tokushima University Institutional Repository) ● Metadata: 115149 (Link to Publication Site) ● Publication site (DOI): 10.1177/1729881417719836 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1177/1729881417719836 (Tokushima University Institutional Repository: 115149, DOI: 10.1177/1729881417719836)
121.	Fuji Ren and Lei Wang : Sentiment analysis of text based on three-way decisions, Journal of Intelligent and Fuzzy Systems, Vol.33, No.1, 245-254, 2017. (Summary) In recent years, affective computing has received much attention in the area of natural language processing and arti cial intelligence. Sentiment orientation recognition of text is one of important parts in affective computing. A methodisproposedtorecognizethemulti-labelsentimentorientationsofChinesetextbasedonthree-waydecisions.Firstly, sentiment orientation and intensity of sentiment words from texts are identi ed by sentiment lexicons, Tongyi Cilin and HowNet.Subsequently,sentimentorientationoftextaredividedintothreedomains,includingpositive,negativeandboundary domain,accordingtotheirsentimentintensityandtheappropriatedecision-makingthresholds.Lastly,sentimentorientations of texts in the boundary domain are distinguished pursuant to sentimental characteristics of sentences in texts. The results of experiments show that the method of multi-label sentiment analysis of Chinese text, based on three-way decisions, is effective for identifying sentiment orientations of texts. (Link to Publication Site) ● Publication site (DOI): 10.3233/JIFS-161522 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.3233/JIFS-161522 (DOI: 10.3233/JIFS-161522)
122.	Hiroki Urakami, Shun Nishide and Fuji Ren : Towards a Developmental Human-Robot Interaction System Using Robot Facial Expressions From Human Feedback, International Journal of Advanced Intelligence (IJAI), Vol.9, No.2, 127-136, 2017. (Summary) Creation of a developmental structure for a human-robot interaction model is essential for practical human robot interaction. We speci cally focus on creating a developmental system of the robot's facial expression based on spoken dialogue of the robot. A humanoid robot Actroid is used to create smooth facial expressions. In the proposed method, we rst create a xed dialogue system with a prede ned facial expression related to each of the robot's dialogue. During communication with a human subject, a feedback (judging if the robot's facial expression was natural or not) is given by the human after the robot's utterance. The facial expression related with the dialogue is changed randomly to a di erent facial expression if the human's feedback denote the robot's expression as unnatural. We constructed the feedback using two types of methods: button pressing and auditory. The actual experiments show that the robot is capable of acquiring natural facial expressions after several communication trials with the human subject. (Keyword) Human robot interaction / Developmental model / Humanoid robot
123.	Kazuyuki Matsumoto, Satoshi Tanaka, Minoru Yoshida, Kenji Kita and Fuji Ren : Ego-state Estimation from Short Texts Based on Sentence Distributed Representation, International Journal of Advanced Intelligence (IJAI), Vol.9, No.2, 145-161, 2017. (Summary) Human personality multilaterally consists of complex elements. Egogram is a method to classify personalities into the patterns according to the combinations of the five levels of ego-states. With recent development of Social Networking Service (SNS), more researches have been trying to judge personality from the statements on SNS. However, there are several problems in the personality judgment based on the superficial information of the statements. Concretely, personality is not always reflected on every statement and the tendency of the statements with influence of personality changes with the times. It is also important to collect sufficient amount of statement data including the results of personality judgment. In this paper, to realize automatic egogram judgement, we focused on the short texts on the SNS, especially microblogs, and represented the comments on Twitter by distributed representation (sentence vector) in the pre-training. Then, we tried to create a model to estimate ego-state level of each user by using a deep neural network. The experimental result showed that our proposed method estimated ego-state with higher accuracy than the baseline method based on bag of words. To investigate the change of personality according to time, we also analyzed how the match rates of the estimation results changed before/after the egogram judgment. Moreover, we confirmed that the personality pattern classification was improved by adding a feature expressing the formal degree of the sentence. (Keyword) Egogram / Personality Estimation / Twitter / Social Networking Service / Distributed Representation (Tokushima University Institutional Repository) ● Metadata: 113455 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1050583647829752704 (Tokushima University Institutional Repository: 113455, CiNii: 1050583647829752704)
124.	Xun Feng, Hongjun Ni and Fuji Ren : Voice conversion based on RBF neural network, International Journal of Advanced Intelligence (IJAI), Vol.9, No.2, 163-173, 2017. (Summary) Recently, voice conversion has becoming the research hotspot, because of its widely application areas. However, the voice conversion technology is still immature. By the researching of existing voice conversion models, the voice conversion system based on the RBF neutral network was designed, and the system simulation was implemented. During conversion, the unvoiced speech was excluded and the voiced speech was reserved. The LPC was the extracted from the source and target speech, then convert the LPC to LSP. The LPS was trained by RBF neural network after time-aligned. Obtained mapping function was used to convert the source LSP to target LSP, and synthesis the speech. Finally, the converted speech evaluated by ABX and MOS to test the tendency and quality of the speech. (Keyword) Voice conversion / RBF / Neutral network
125.	Min Hu, Yaona Zheng, Xiaoyin Huang and Fuji Ren : FacialExpressionRecognitionBasedonMonogenicMulti-featureandFused SparseRepresentation, International Journal of Advanced Intelligence (IJAI), Vol.9, No.1, 111-126, 2017. (Summary) In the eld of facial expression recognition, in order to make up for insuf cient information of monogenic magnitude and orientation which is extracted by monogenic binary pattern, and enhance robustnessofsparseclassi erforfacialexpressionclassi cation,afacialexpressionrecognitionmethodbased on monogenic multi-feature and fused sparse representation is proposed in this paper. First of all, the preprocessed images of facial expression are ltered by the monogenic signal with the purpose of acquiringtheinformationofmonogenicmagnitude,orientation,andphase.Secondly,wefusemagnitude, orientation and phase information with the method of monogenic binary pattern, monogenic oriented gradient, and enhanced monogenic phase respectively, to form different expression features and construct the corresponding classi ers. Finally facial expression recognition is completed by using the regularized least-square theory to optimize the weight of double classi er. Experiments are performed on JAFFE and Cohn-Kanade facial expression databases and the average rates reach up to 97.30% and 99.33% respectively. The results of experiments show that the proposed method effectively improves the recognition ef ciency of facial expression. (Keyword) Monogenic multi-feature / sparse representation / facial expression recognition
126.	Shun Nishide, Hidenobu Shibasaki, XIN KANG and Fuji Ren : Generation of Humanlike Facial Expression for Natural Human-Robot Interaction System, International Journal of Advanced Intelligence (IJAI), Vol.9, No.1, 77-65, 2017. (Summary) Recognition and expression of emotions are indispensible functions for robots intended to play a role in the human society. Among various modalities, facial expression is said to be one of the most important factors for represent emotions. In this paper, we present our work on creating humanlike facial expressions for the humanoid robot Actroid, and adapting it to actual human-robot interaction scenario. Facial expressions were created manually using the software Wten source code, by adjusting parameters of facial features. The created expressions were implemented in a xed dialogue between a human and robot. Experiments were conducted with human subjects talking with the robot. Evaluations were done using questionaires on naturalness and e ectiveness of facial expressions during the dialogue. (Keyword) Human robot interaction / Facial expression / Humanoid robot
127.	Jiawen Deng, Mingyu Huang and Fuji Ren : Text Classification Based on Word Co-occurrence with Background knowledge, International Journal of Advanced Intelligence (IJAI), Vol.9, No.1, 29-42, 2017. (Summary) This article proposes a data treatment strategy to generate a new text representation model with discriminative feature for the sake of text classification. This feature is determined by word co-occurrence information, and is extracted by measuring the cosine similarity between word co-occurrence vectors of testing documents and background knowledge in Chinese language. The background knowledge is composed by the word co-occurrence matrix of all words in background corpus based on top n keywords in each category which selected by TFIDF value. This strategy is to get discriminative features to reduce the ambiguity and noise inherent of the traditional representation model. In the experiments, using a linear SVM classifier, we investigate the effects of the proposed method with two Chinese classification corpora, and two background corpora are used as background knowledge. Results show that, compared with conventional method, the proposed strategy performs better in the values of precision, recall and F1 score. (Keyword) Text classification / text representation / word co-occurrence / background knowledge
128.	XIN KANG, Yunong Wu and Fuji Ren : Disambiguating Users' Temporal Intent in Search Queries with Deep Neural Networks, International Journal of Advanced Intelligence (IJAI), Vol.9, No.1, 11-28, 2017.
129.	Xiao Sun, Fuji Ren and Jiaqi Ye : Trends Detection of Flu based on Essemble Models with Emotional Factors from Social Networks, IEEJ Transactions on Electrical and Electronic Engineering (TEEE), Vol.12, No.3, 388-396, 2017. (Summary) In uenza is an acute respiratory illness and widespread activity that occurs every year. Detection and prevention of in uenza in its earliest stage would reduce the spread range of the illness. Sina microblog is a popular microblogging service in China, which can be treated as perfect reference sources for u detection because of its real-time character. A large number of active users post about their daily life continually. In this paper, we investigate the real-time u detection problem and propose a u detection model with emotion factors and semantic information. First, we extract u-related microblog posts automatically in real time by adopting support vector machine (SVM) lter and semantic features. We use association rule mining to extract strongly associated features as additional features for posts to overcome the limitation of 140 words, including sentiment information, which can help us to classify the posts without u-related features. Then, the conditional random eld model is revised and applied to detect the transition time of u so that we can nd out which place is more likely to have in uenza outbreak and when it is more likely to have in uenza outbreak in a city or province in China. Experimental results on detecting u situation during certain times in some locations show the robustness and effectiveness of the proposed model, which might help health authorities in predicting u outbreak ahead and take timely control action and response. (Link to Publication Site) ● Publication site (DOI): 10.1002/tee.22389 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1002/tee.22389 (DOI: 10.1002/tee.22389)
130.	Yiming Tang and Fuji Ren : Fuzzy Systems Based on Universal Triple I Method and Their Response Functions, International Journal of Information Technology & Decision Making, Vol.16, No.2, 443-471, 2017. (Summary) The fuzzy systems based on the universal triple I method are investigated, and then theirresponse functions are analyzed. First, the conclusions show that 100 fuzzy systems via theuniversal triple I method are approximately interpolation functions, which can be used inpractical systems, and that 90 ones are approximately ¯tted functions, which may be usable.Second, as its special cases, the Compositional Rule of Inference (CRI) method and the triple Imethod are discussed, with the results that 19 fuzzy systems via the CRI method and 2 ones viathe triple I method are practicable. Therefore, the universal triple I method has larger e®ectivechoosing space, which can obtain more usable fuzzy systems than the others. Lastly, it is foundthat the ¯rst implication and second implication, respectively, embody the function of rule baseand reasoning mechanism, further demonstrating the reasonability of the universal triple Imethod. (Link to Publication Site) ● Publication site (DOI): 10.1142/S0219622014500746 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1142/S0219622014500746 (DOI: 10.1142/S0219622014500746)
131.	Xiaohua Wang, Dengyong Hou, Min Hu and Fuji Ren : Dual-modality emotion recognition based on composite spatio-temporal features, Journal of Image and Graphics, Vol.22, No.1, 39-48, 2017. (Summary) Objective In view of existing algorithms, volume local binary pattern is applied to the feature extraction of video frames. However, problems such as large feature dimension, weak robustness to illumination, and noise exist. This study proposes a new feature description algorithm, which is temporal-spatial local ternary pattern moment. This algorithm introduces three value patterns, and it is extended to the temporal-spatial series to describe the variety of pixel values among adjacent frames. The value of texture feature is represented by the energy values of the three value model matrixes, which are calculated according to the gray-level co-occurrence matrix. Considering that the temporal-spatial local ternary pattern moment only describes the texture feature, it lacks the expression of image edge and direction information. Therefore, it cannot fully describe the characteristics of emotional videos. The feature of 3D histograms of oriented gradients is further fused to enhance the description of the emotion feature. Composite spatio-temporal features are obtained by combining two different features. Method First, the emotional videos are preprocessed, and five frame images are obtained by K mean clustering, which are used as the expression and body posture emotion sequences. Second, TSLTPM and 3DHOG features are extracted from the expression and gesture emotion sequences, and the minimum Euclidean distance of the feature between the test sequence and labeled emotion training set is calculated. The calculated value is used as independent evidence to construct the basic probability assignment function. Finally, according to the rules of D-S evidence theory, the expression recognition result is obtained by fused BPA. Result Experimental results on the bimodal expression and body posture emotion database show that complex spatio-temporal features exhibit good recognition performance. The average recognition rates of 83.06% and 94.78% are obtained in the single model identification of facial expressions and gestures, respectively, compared with other algorithms. The average recognition rate of the single-expression model is 9.27%, 12.89%, 1.87%, and 1.13% higher than those of VLBP, LBP-TOP, TSLTPM, and 3DHOG, respectively. The average recognition rate of the single-gesture model is 24.61%, 27.55%, 1.18%, and 0.98% higher than those of VLBP, LBP-TOP, TSLTPM, and 3DHOG, respectively. The average recognition rate after the fusion of these two models is 96.86%, which is higher than the rate obtained by a single model. This result confirms the effectiveness of emotion recognition under the fusion of expression and gesture. Conclusion The TSLTPM feature proposed in our paper extends the VLBP, which is effective in describing the local features of video images, into the temporal-spatial local ternary pattern. The proposed feature has low dimensionality, and it can enhance the robustness to illumination and noise. The composite spatio-temporal features fused with 3DHOG and TSLTPM can fully describe the effective information of emotional videos, and it enhances the classification performance of such videos. The effectiveness of the proposed algorithm in comparison with other typical feature extraction algorithms is also demonstrated. The proposed algorithm is proven suitable for identifying the emotion of static background videos, and the superiority of the fusion method in this study is verified. (Keyword) 俗語 / トピック分析 / 時系列分析 (Link to Publication Site) ● Publication site (DOI): 10.11834/jig.20170105 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.11834/jig.20170105 (DOI: 10.11834/jig.20170105)
132.	Min Hu, Zixi Yu, Xiaohua Wang, Fuji Ren and Lei He : G-LBP and Variance Cross Projection Function for Face Recognition, Journal of Graphics, Vol.38, No.1, 82-89, 2017. (Summary) In order to enhance robustness of traditional Gabor features towards illumination, expression and pose variance and overcome its high dimension problem, the paper proposes a face recognition method based on Gabor, local binary patter and variance projection entropy improved algorithm. First, the multi direction multi-scale fusion Gabor image is coded with LBP, and the coded image fused and the histograms of image block calculated. Second, a local projection entropy feature extraction is adopted for face images with anti-geometric distortion variance projection entropy and cross variance projection entropy operator. Finally, the face recognition is completed by using BP neutral network to fuse and make decision weightily. The G-LBP feature extraction reduces the redundancy of data greatly, and maintains the integrity of the effective information. Variance projection of entropy and cross entropy improves the richness of the feature. The weighted fusion in decision-making layer plays an important role of integration between the classifiers and improves the recognition rate of face recognition. Compared with other literature algorithms, experiment results verify the effectiveness and superiority of the proposed algorithm. (Link to Publication Site) ● Publication site (DOI): 10.11996/JG.j.2095-302X.2017010082 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.11996/JG.j.2095-302X.2017010082 (DOI: 10.11996/JG.j.2095-302X.2017010082)
133.	Xiao Sun, Chongyuan Sun, Changqin Quan, Fuji Ren, Fang Tian and Kunxia Wang : Fine-Grained Emotion Analysis Based on Mixed Model for Product Review, International Journal of Networked and Distributed Computing, Vol.5, No.1, 1-11, 2017. (Summary) Nowadays, with the rapid development of B2C e-commerce and the popularity of online shopping, the Web storages huge number of product reviews comment by customers. A large number of reviews made it difficult for manufacturers or potential customers to track the comments and suggestions that customers made. This paper presents a method for extracting emotional elements containing emotional objects and emotional words and their tendencies from product reviews based on mixed model. First we constructed conditional random fields to extract emotional elements, lead-in semantic and word meaning as features to improve the robustness of feature template and used rules for hierarchical filtering errors. Then we constructed support vector machine to classify the emotional tendency of the fine-grained elements to achieve key information from product reviews. Deep semantic information imported based on neural network to improve the traditional bag of word model. Experimental results show that the proposed model with deep features efficiently improved the F-Measure. (Keyword) 俗語 / トピック分析 / 時系列分析 (Tokushima University Institutional Repository) ● Metadata: 115156 (Link to Publication Site) ● Publication site (DOI): 10.2991/ijndc.2017.5.1.1 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.2991/ijndc.2017.5.1.1 (Tokushima University Institutional Repository: 115156, DOI: 10.2991/ijndc.2017.5.1.1)
134.	Zhong Huang and Fuji Ren : Facial expression recognition method based on multi-regional D-S evidences theory fusion, IEEJ Transactions on Electrical and Electronic Engineering (TEEE), 2016. (Summary) To achieve decision-level fusion of multi-regional features and highlight the credibility of different regional evidences, a facial expression recognition method based on multi-regional evidence fusion is proposed. A block histogram of gradient Gabor features in three regions, namely eyebrows, eyes, and mouth, is extracted from a facial image and regarded as evidence in expression classification. Then, category membership and regional contribution are solved with the region-weighted semisupervised fuzzy c-means clustering algorithm to construct initial basic probability assignment (BPA) and emphasize the importance of different evidences, respectively. The initial BPA of evidence is further reassigned by combining region contribution and evidence supportability to reduce evidential conflict. Finally, the final decision-level fusion of multi-regional evidences is obtained based on the Dempster Shafer (D S) combination rule. The experimental results for the Cohn Kanade expression database show that the BPA construction method based on category-membership degree and the reassignment strategy based on region contribution and evidence supportability improves the recognition rate and maintains good robustness for all types of expressions. Compared with existing decision-level fusion strategies and classification methods, the proposed recognition framework based on D S evidences theory has the advantages in recognition performance and reliability, particularly in increasing the recognition rate for expressions that are difficult to distinguish, such as fear, sadness, and disgust. (Link to Publication Site) ● Publication site (DOI): 10.1002/tee.22372 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1002/tee.22372 (DOI: 10.1002/tee.22372)
135.	Xiaohua Wang, Xinyue Liu, Lingyun Li, Fuming Zhang, MIn Hu and Fuji Ren : GlycCompSoft: Software for Automated Comparison of Low Molecular Weight Heparins Using Top-Down LC/MS Data, PLoS ONE, Vol.11, No.12, 2016. (Summary) Low molecular weight heparins are complex polycomponent drugs that have recently become amenable to top-down analysis using liquid chromatography-mass spectrometry. Even using open source deconvolution software, DeconTools, and automatic structural assignment software, GlycReSoft, the comparison of two or more low molecular weight heparins is extremely time-consuming, taking about a week for an expert analyst and provides no guarantee of accuracy. Efficient data processing tools are required to improve analysis. This study uses the programming language of Microsoft Excel™ Visual Basic for Applications to extend its standard functionality for macro functions and specific mathematical modules for mass spectrometric data processing. The program developed enables the comparison of top-down analytical glycomics data on two or more low molecular weight heparins. The current study describes a new program, GlycCompSoft, which has a low error rate with good time efficiency in the automatic processing of large data sets. The experimental results based on three lots of Lovenox®, Clexane® and three generic enoxaparin samples show that the run time of GlycCompSoft decreases from 11 to 2 seconds when the data processed decreases from 18000 to 1500 rows. (Keyword) 俗語 / トピック分析 / 時系列分析 (Tokushima University Institutional Repository) ● Metadata: 112311 (Link to Publication Site) ● Publication site (DOI): 10.1371/journal.pone.0167727 (Link to Search Site for Scientific Articles) ● PubMed @ National Institutes of Health, US National Library of Medicine (PMID): 27942011 ● Summary page in Scopus @ Elsevier: 2-s2.0-85006251852 (Tokushima University Institutional Repository: 112311, DOI: 10.1371/journal.pone.0167727, PubMed: 27942011, Elsevier: Scopus)
136.	Chao Li, Fuji Ren and XIN KANG : Selectional Preferences Based on Distributional Semantic Model, WSEAS Transactions on Computers, Vol.15, 258-264, 2016. (Summary) In this paper, we propose a approach based on distributional semantic model to the selectional preference in the verb & dobj (direct object) relationship. The distributional representations of words are employed as the semantic feature by using theWord2Vec algorithm. The machine learning method is used to build the discrimination model. Experimental results show that the proposed approach is effective to discriminate the compatibility of the object words and the performance could be improved by increasing the number of training data. By comparing the previous method, the proposed method obtain the promising results with obvious improvement. Moreover, the results demonstrate that the semantics is an universal, effective and stable feature in this task, which is consistent with our awareness of using words. (Tokushima University Institutional Repository) ● Metadata: 118263 (Tokushima University Institutional Repository: 118263)
137.	Xiaohua Wang, Dengyong Hou, Min Hu and Fuji Ren : Dual-modality Emotion Recognition Model Based on Temporal-spatial LBP Moment and Dempster-Shafer Evidence Fusion, Opto-Electronic Engineering, Vol.43, No.12, 154-161, 2016. (Link to Publication Site) ● Publication site (DOI): 10.3969/j.issn.1003-501X.2016.12.024 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.3969/j.issn.1003-501X.2016.12.024 (DOI: 10.3969/j.issn.1003-501X.2016.12.024)
138.	Fuji Ren and Xiao Sun : Current Situation and Development of Intelligence Robots, ZTE, Vol.14, No.S1, 25-34, 2016. (Summary) Industrial intelligent robots are treated as a measure of na tionalscientificlevelandtechnologyinnovation,andalsothe important symbol of high level manufacturing, while service intelligent robots can directly affect people's daily lives. The development of artificial robots in different areas is at tracting much attention around the world. This article re views the current situation and development of Chinese and internationalintelligentrobotmarketsincludingindustrialro botsandservicerobots.Theintelligentrobottechnologyand theclassificationofrobotsarealsodiscussed.Finally,appli cations of intelligent robots in various fields are concluded andthedevelopmenttrendsandoutlookofintelligentrobots areexplored. (Keyword) intelligentrobot / artificialintelligence / developmenttrends (Link to Publication Site) ● Publication site (DOI): 10.3969/j.issn.16735188.2016.S1.005 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.3969/j.issn.16735188.2016.S1.005 (DOI: 10.3969/j.issn.16735188.2016.S1.005)
139.	Fuji Ren and Zhong Huang : Automatic Facial Expression Learning Method Based on Humanoid Robot XIN-REN, IEEE Transactions on Human-Machine Systems, Vol.46, No.6, 810-821, 2016. (Summary) The ability of a humanoid robot to display human-like facial expressions is crucial to the natural human computer interaction. To fulfill this requirement for an imitative humanoid robot, XIN-REN, an automatic facial expression learning method is proposed. In this method, first, a forward kinematics model, which is designed to reflect nonlinear mapping relationships between servo displacement vectors and corresponding expression shape vectors, is converted into a linear relationships between the mechanical energy of servo displacements and the potential energy of feature points, based on the energy conservation principle. Second, an improved inverse kinematics model is established under the constraints of instantaneous similarity and movement smoothness. Finally, online expression learning is employed to determine the optimal servo displacements for transferring the facial expressions of a human performer to the robot. To illustrate the performance of the proposed method, we conduct evaluation experiments on the forward kinematics model and the inverse kinematics model, based on the data collected from the robot's random states as well as fixed procedures by animators. Further, we evaluate the facial imitation ability with different values of the weighting factor, according to three sequential indicators (space-similarity, time-similarity, and movement smoothness). Experimental results indicate that the deviations in mean shape and position do not exceed 6 pixels and 3 pixels, respectively, and the average servo displacement deviation does not exceed 0.8%. Compared with other related studies, the proposed method maintains better space time similarity with the performer, besides ensuring smoother trajectory for multiframe sequential imitation. (Keyword) movement smoothness / Expression mapping / forward kinematics model / humanoid robot / inverse kinematics model / movement similarity (Link to Publication Site) ● Publication site (DOI): 10.1109/THMS.2016.2599495 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85027498565 (DOI: 10.1109/THMS.2016.2599495, Elsevier: Scopus)
140.	Xiao Sun, Fei Gao and Fuji Ren : Mining the impact of social news on the emotions of users based on Deep Model, Journal of Chinese Information Processing, 29-32, 2016. (Summary) This work investigates the deep features in social news which can influence the emotions of people.Three kinds of feature compression methods are used to extract shallow features from the granularities of unigram word,bigram word and theme.The work used Support Vector Machine to select the optimal shallow features of three granularities,and the optimal F1_macro are 60.5% 62.1% 63.3% separately.The work introduced Deep Belief Network (DBN) model to train and abstract the optimal shallow features,so we can get the deep features.The optimal F1_macro of DBN3 are 61.4% 63.5% 66.1% respectively.The experimental results show that the deep features abstracted by Deep Belief Network have more semantic information and better performance than shallow features in determining the influence on people's emotions by social news. (Keyword) Deep Belief Nets / Restricted Boltzmann Machine / Impacts on Emotion / Social News (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS.2014.7175698 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84948460907 (DOI: 10.1109/CCIS.2014.7175698, Elsevier: Scopus)
141.	Xiao Sun, Zhongyuan Sun and Fuji Ren : Biomedical Named Entity Recognition Based on Deep Conditional Random Fields, Moshi Shibie yu Rengong Zhineng/Pattern Recognition and Artificial Intelligence, Vol.29, No.11, 997-1008, 2016. (Link to Publication Site) ● Publication site (DOI): 10.16451/j.cnki.issn1003-6059.201611005 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.16451/j.cnki.issn1003-6059.201611005 (DOI: 10.16451/j.cnki.issn1003-6059.201611005)
142.	Xiao Sun, Jiajin He and Fuji Ren : Ironically linguistic judgement based on hybrid neural network model via multi-feature fusion, Journal of Chinese Information Processing, Vol.30, No.6, 37-45, 2016.
143.	Xiaohua Wang, Ruijing Li, Min Hu and Fuji Ren : Occluded facial expression recognition based on the fusion of local features, Journal of Image and Graphics, Vol.21, No.11, 1473-1482, 2016. (Summary) To reduce the effect of partial occlusion in facial expression recognition, this paper proposes a new method of facial expression recognition based on local feature fusion. Method First, the normalized images are processed by the Gaussian filter to reduce the effect of noise. According to their different contributions in facial expression recognition, all the images are then divided into two main parts: near the eye and near the mouth. To analyze considerable structure detail, these two parts are further divided into several non-overlapping blocks. The following two patterns are used to extract the features of each sub block: the difference center-symmetric local binary pattern, which is the change of center-symmetric local binary pattern; and the gradient center-symmetric local directional pattern, which is the change of difference local directional pattern. The features are marked as two binary sequences, which are then cascaded to obtain the characteristic histogram of the sub block. The final histogram of the image is obtained by cascading the histogram of each sub block. Finally, the nearest neighbor method is used for classification. Chi-square distance is used to calculate the distance among the characteristic histograms of the testing and training images. Considering the difference of the amount of information contained in each sub block and to reduce the effect of occlusion further, information entropy is used to weigh chi-square distance adaptively. Result Three cross experiments are conducted on JAFFE and CK databases. The average recognition accuracies in random occlusion, mouth occlusion, and eye occlusion cases are 92.86%, 94.76%, and 86.19% on JAFFE database, and are 99%, 98.67%, and 99% on CK database. Conclusion In the aspect of feature extraction, our method describes the image from two aspects: one is the difference of the pixel values in the gradient direction, and the other is the difference of the edge response values between gradient directions. Accordingly, the image can be fully described. In the aspect of occlusion, image segmentation and information entropy are used to weigh chi-square distance adaptively. Thus, our method can effectively reduce the effect of occlusion. Under the same experimental conditions, experimental results show the effectiveness and superiority of the proposed method to other classical local feature extraction and occlusion handling methods. (Link to Publication Site) ● Publication site (DOI): 10.11834/jig.20161107 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.11834/jig.20161107 (DOI: 10.11834/jig.20161107)
144.	Yu Gu, Fuji Ren and Jie Li : PAWS: Passive Human Activity Recognition Based on WiFi Ambient Signals, IEEE Internet of Things Journal, Vol.3, No.5, 796-805, 2016. (Summary) Indoor human activity recognition remains a hot topic and receives tremendous research efforts during the last few decades. However, previous solutions either rely on special hardware, or demand the cooperation of subjects. Therefore, the scalability issue remains a great challenge. To this end, we present an online activity recognition system, which explores WiFi ambient signals for RSSI (Received Signal Strength Indicator) fingerprint of different activities. It can be integrated into any existing WLAN networks without additional hardware support. Also it does not need the subjects to be cooperative during the recognition process. More specifically, we first conduct an empirical study to gain in-depth understanding of WiFi characteristics, e.g., the impact of activities on the WiFi RSSI. Then, we present an online activity recognition architecture that is flexible and can adapt to different settings/conditions/scenarios. Lastly, a prototype system is built and evaluated via extensive real-world experiments. A novel fusion algorithm is specifically designed based on the classification tree to better classify activities with similar signatures. Experimental results show that the fusion algorithm outperforms three other well-known classifiers (i.e., NaiveBayes, Bagging and k-NN) in terms of accuracy and complexity. Important sights and hands-on experiences have been obtained to guide the system implementation and outline future research directions. (Keyword) WiFi / activity recognition / ambient signals / fusion algorithm (Link to Publication Site) ● Publication site (DOI): 10.1109/JIOT.2015.2511805 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/JIOT.2015.2511805 (DOI: 10.1109/JIOT.2015.2511805)
145.	Wei Wang, Xia Zhu, Fang Fang, Zhenlu Qin, Erhui Guo and Fuji Ren : Optimal design of 3D chip scan chains based on cores-hierarchical-placement, Journal of Electronic Measurement and Instrument, Vol.30, No.10, 1482-1489, 2016. (Link to Publication Site) ● Publication site (DOI): 10.13382/j.jemi.2016.10.005 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.13382/j.jemi.2016.10.005 (DOI: 10.13382/j.jemi.2016.10.005)
146.	Jun Liu, Tangya Wang and Fuji Ren : Bad-Die Recycling Technique for Yield Enhancement of Three-Dimensional Memories, Microelectronics & Computer, Vol.33, No.10, 7-12, 2016. (Link to Publication Site) ● Publication site (DOI): 10.19304/j.cnki.issn1000-7180.2016.10.002 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.19304/j.cnki.issn1000-7180.2016.10.002 (DOI: 10.19304/j.cnki.issn1000-7180.2016.10.002)
147.	Xiao Sun, Chengcheng LI and Fuji Ren : Sentiment Analysis for Chinese Microblog based on Deep Neural Networks with Convolutional Extension Features, Neurocomputing, Vol.210, 227-236, 2016. (Summary) Related research for sentiment analysis on Chinese microblog is aiming at the analysis procedure of posts. The length of short microblog text limits feature extraction of microblog. Tweeting is the process of communication with friends, so that microblog comments are important reference information for related post. A contents extension framework is proposed in this paper combining posts and related comments into a microblog conversation for features extraction. A novel convolutional auto encoder is adopted which can extract contextual information from microblog conversation as features for the post. A customized DNN(Deep Neural Network) model, which is stacked with several layers of RBM (Restricted Boltzmann Machine), is implemented to initialize the structure of neural network. The RBM layers can take probability distribution samples of input data to learn hidden structures for better high level features representation. A ClassRBM (Classification RBM) layer, which is stacked on top of RBM layers, is adopted to achieve the final sentiment classification label for the post. Experimental results show that, with proper structure and parameters, the performance of proposed DNN on sentiment classification is better than state of the art surface learning models such as SVM or NB, which proves that the proposed DNN model is suitable for short-length document classification with proposed feature dimensionality extension method. (Keyword) Deep Neural Network / Sentiment analysis / Microblog conversation / Restricted Boltzmann Machine / ClassRBM (Link to Publication Site) ● Publication site (DOI): 10.1016/j.neucom.2016.02.077 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1016/j.neucom.2016.02.077 (DOI: 10.1016/j.neucom.2016.02.077)
148.	Yu Gu, Lianghu Quan and Fuji Ren : AAH: accurate activity recognition of human beings using WiFi signals, Concurrency and Computation : Practice & Experience, Vol.28, No.14, 3910-3926, 2016. (Summary) The flourishing social networks nowadays have greatly enriched our ways of communications and thus brought people in the world much closer than ever. However, critical contexts of the traditional face-to-face communications, for example, body gestures, could be missing during the online communication, hampering the user experiences. To fill in the blank, this paper presents a passive and devices-free activity recognition system, by harvesting fingerprints of different activities from ubiquitous WiFi signals. It can be integrated into any existing WLAN networks without additional hardware supports. Also, it does not need the subjects to be cooperative during the recognition process. A prototype system is built and evaluated via extensive real-world experiments. By comparing with three state-of-the art solutions, that is, K-nearest neighbor, naive Bayes, and bagging, we show the superiority of the proposed method in terms of accuracy and complexity. (Keyword) accurate activity recognition / WiFi signals / fusion algorithm (Link to Publication Site) ● Publication site (DOI): 10.1002/cpe.3741 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84983120485 (DOI: 10.1002/cpe.3741, Elsevier: Scopus)
149.	Fuji Ren, Yanqiu Li, Min Hu and Liangfeng Xu : Face Recognition Method Based on Multi Features Description and Local Fusion Classification Decision, Opto-Electronic Engineering, Vol.43, No.9, 82-89, 2016. (Link to Publication Site) ● Publication site (DOI): 10.3969/j.issn.1003-501X.2016.09.001 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84988517652 (DOI: 10.3969/j.issn.1003-501X.2016.09.001, Elsevier: Scopus)
150.	Yiming Tang and Fuji Ren : Variable Differently Implicational Inference for R- and S-Implications, International Journal of Information Technology & Decision Making, Vol.15, No.5, 1235-1264, 2016. (Summary) As a generalization of the compositional rule of inference (CRI) algorithm and the fully implicational algorithm, the differently implicational algorithm of fuzzy inference not only inherit the advantages of the fully implicational algorithm, but also has stronger practicability. Then, the variable differently implicational algorithm was proposed to make the current differently implicational algorithms compose a united whole. In this paper, the variable differently implicational algorithm is further researched focusing on the fuzzy modus tollens (FMT) problem. The differently implicational principle for FMT is improved. Moreover, the unified solutions of the variable differently implicational algorithm for FMT are accomplished for R- and S-implications. Following that, as an important index of fuzzy inference, the continuity of this algorithm is analyzed for main R- and S-implications, in which excellent performance is obtained. Finally, its optimal solutions as well as inference examples are provided for several specific R- and S-implications. (Keyword) Fuzzy inference / fuzzy modus tollens / fuzzy implication / compositional rule of inference (Link to Publication Site) ● Publication site (DOI): 10.1142/S0219622016500334 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1142/S0219622016500334 (DOI: 10.1142/S0219622016500334)
151.	Fei Gao, Xiao Sun, Kunxia Wang and Fuji Ren : Chinese micro-blog sentiment analysis based on semantic features and PAD model, 15th IEEE/ACIS International Conference on Computer and Information Science, 2016. (Summary) With the increasing impact of social networks, microblog becomes important carrier of information and social interaction for human beings, which contains emotional states that have important research significance. We try to analysis the microblog text with the methods of emotional vocabulary, combining domain knowledge of psychology and affective computing, continuous dimension of emotion psychology PAD model which is adopted as basis of sentiment analysis. Emotional state inherent in the text is analyzed to obtain a more accurate result and achieve purposes of emotional analysis. At the same time, to achieve emotional microblog text computability from the aspect of personal characteristics. Experimental results show that the method can improve the microblog text sentiment analysis accuracy and precision. The method is able to get a good application in the different themes and different emotional features. (Keyword) 俗語 / トピック分析 / 時系列分析 (Link to Publication Site) ● Publication site (DOI): 10.1109/ICIS.2016.7550903 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84988005899 (DOI: 10.1109/ICIS.2016.7550903, Elsevier: Scopus)
152.	Xiao Sun, Xiaoqi Peng and Fuji Ren : Detect the Emotions of Whe Public Based on Cascade Neural Network Model, 15th IEEE/ACIS International Conference on Computer and Information Science, 2016. (Keyword) 俗語 / トピック分析 / 時系列分析 (Link to Publication Site) ● Publication site (DOI): 10.1109/ICIS.2016.7550901 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/ICIS.2016.7550901 (DOI: 10.1109/ICIS.2016.7550901)
153.	Xiao Sun, Chongyuan Sun, Fuji Ren, Fang Tian and Kunxia Wang : Emotional Element Detection and Tendency Judgment Based on Mixed Model with Deep Features, 15th IEEE/ACIS International Conference on Computer and Information Science, 2016. (Keyword) 俗語 / トピック分析 / 時系列分析 (Link to Publication Site) ● Publication site (DOI): 10.1109/ICIS.2016.7550779 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84987968711 (DOI: 10.1109/ICIS.2016.7550779, Elsevier: Scopus)
154.	Fuji Ren, Yu Wang and Changqin Quan : A novel factored POMDP model for affective dialogue management, Journal of Intelligent and Fuzzy Systems, Vol.31, No.1, 127-136, 2016. (Summary) Partially observable Markov decision process (POMDP) model has been demonstrated many times to be suited for robust spoken dialogue management. Recently, some factored representations of POMDP model are designed for specific dialogue tasks. This paper proposes a novel factored POMDP model to describe a new application of affective dialogue management. Different from existing models, the user's state space and the system's observation space are both divided into two distinct components: goal and emotion. Moreover, the system's action space is for the first time factored into two parts, i.e., goal response and emotion response, and the reward function is accordingly updated by weighted sum of the two-part rewards. An example of intelligent music player is given to explain how to apply the new model to build an affective dialogue system. Four experiments are designed to reveal the influence of key parameters on the system performance. The simulation results demonstrate the rationality and feasibility of the proposed model. (Keyword) Dialogue management / POMDP model / affective computing / spoken dialogue system (Link to Publication Site) ● Publication site (DOI): 10.3233/IFS-162126 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.3233/IFS-162126 (DOI: 10.3233/IFS-162126)
155.	Xiao Sun, Ting Pan and Fuji Ren : Facial Expression Recognition Using ROI-KNN Deep Convolutional Neural Networks, ACTA AUTOMATICA SINICA, Vol.42, No.6, 883-891, 2016. (Summary) Deep neural networks have been proved to be able to mine distributed representation of data including image, speech and text. By building two models of deep convolutional neural networks and deep sparse recti¯er neural networks on facial expression dataset, we make contrastive evaluations in facial expression recognition system with deep neural networks. Additionally, combining region of interest (ROI) and K-nearest neighbors (KNN), we propose a fast and simple improved method called OI-KNN" for facial expression classi¯cation, which relieves the poor generalization of deep neural networks due to lacking of data and decreases the testing error rate apparently and generally. The proposed method also improves the robustness of deep learning in facial expression classi¯cation. (Keyword) Convolution neural networks / facial expression recognition / model generalization / prior knowledge (Link to Publication Site) ● Publication site (DOI): 10.16383/j.aas.2016.c150638 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.16383/j.aas.2016.c150638 (DOI: 10.16383/j.aas.2016.c150638)
156.	Fuji Ren and Chao Li : Hybrid Chinese Text Classification Approach Using General Knowledge from Baidu Baike, IEEJ Transactions on Electrical and Electronic Engineering (TEEE), Vol.11, No.5, 488-498, 2016. (Summary) Most of the previous studies focused on enriching text representation to address text classi cation (TC) task. However, conventional classi cation approaches with VSM (vector space model) on Chinese text study intensively only the words and their relationship in some speci c corpus/dataset but ignore the basic concept of categories and the general knowledge behind the words learned and used to recognize entities by people. This paper focuses on enriching text representation and proposes a novel approach, which complements information from the online Chinese encyclopedia Baidu Baike for Chinese TC. The similarities between every text and each concept of categories and the most related words from Baidu Baike are added to the feature space. The performance of the proposed approach is measured on the Fudan University TC corpus, which is an imbalanced Chinese dataset. In the experiments, the proposed Baidu Baike-based concept similarity approach obtains promising results when compared with a previous research and the conventional method, with macro-precision of 90.31%, recall of 75.45%, and F1 score 80.32%, which are about 0.02%, 0.15%, 0.12%, respectively, higher than the conventional method, which obviously improves the recall for some small categories while keeping precision at high level and improving the macro F1 score. Moreover, the proposed approach has good expandability, so that many other knowledge bases could be integrated and many other concepts could be referred to improve the effectiveness. (Keyword) Baidu Baike / Chinese / general knowledge / support vector machine / text classi cation / text representation (Link to Publication Site) ● Publication site (DOI): 10.1002/tee.22266 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84969942263 (DOI: 10.1002/tee.22266, Elsevier: Scopus)
157.	Xiao Sun, Jiaqi Yi and Fuji Ren : Detecting Influenza States based on Hybrid Model with Personal Emotional Factors from Social Networks, Neurocomputing, Vol.210, 257-268, 2016. (Summary) In this paper, we exhibit how social media data can be used to detect and analyze real-word phenomena with several data mining techniques. We investigate the real-time flu detection problem and propose a flu state detection model with personal emotional factors and semantic information (Em-Flu model). First, we extract flu-related microblog posts automatically in real-time using a hybrid model composed by Support Vector Machine with features extracted from Restricted Boltzmann Machine. In order to overcome the limitation of 140 words for posts, expect for sentiment related features, association semantic rules are also adopted as additional features, such as bag of words, negative words, degree adverbs and sentiment words dictionary. For flu state detection at specific location, we propose an unsupervised model based on personal emotional factors to figure out what state of flu in specific place. For comparison, a supervised model is also built by adopting Conditional Random Fields to decide whether a poster has ``really'' catch flu and what influenza stage the poster is in. Some statistic methods and prior rules are adopted in supervised model to get the flu state of specific locations by counting the number of microblog posts in different flu states. By considering personal emotional factors, spatial features and temporal patterns of influenza, the performance of unsupervised and supervised models are both improved. The system could tell when and where influenza epidemic is more likely to occur at certain time in specific locations. In different experiments results, the hybrid models show robustness and effectiveness than state-of-the-art unsupervised and supervised model only considering the number of posts. (Keyword) Influenza detection / Personal emotional factors / Transition time detection / Social web mining / Hybrid model (Link to Publication Site) ● Publication site (DOI): 10.1016/j.neucom.2016.01.107 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1016/j.neucom.2016.01.107 (DOI: 10.1016/j.neucom.2016.01.107)
158.	Sun Yan, Fuji Ren, XIN KANG and Changqin Quan : Developing a Japanese Adverb-Emotion Corpus to Investigate the Effect of Adverbs in Japanese Sentence Emotion Classification, International Journal of Advanced Intelligence (IJAI), Vol.8, No.1, 99-116, 2016. (Keyword) adverb emotion / emotion feature / emotion corpus / emotion classification
159.	Fuji Ren, Yanqiu Li, Liangfeng Xu, Min Hu and Xiaohua Wang : Face recognition method based on local mean pattern description and double weighted decision fusion for classification, Journal of Image and Graphics, Vol.21, No.5, 565-573, 2016. (Keyword) face recognition / local mean pattern / double weighted decision fusion / cloud model (Link to Publication Site) ● Publication site (DOI): 10.11834/jig.20160504 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.11834/jig.20160504 (DOI: 10.11834/jig.20160504)
160.	Tian Chen, Xin Yi, Wei Wang, Jun Liu, Huaguo Liang and Fuji Ren : Low Power Multistage Test Data Compression Scheme, ACTA ELECTRONICA SINICA, Vol.44, No.4, 241-247, 2016. (Link to Publication Site) ● Publication site (DOI): 10.3969/j.issn.0372-2112.2016 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.3969/j.issn.0372-2112.2016 (DOI: 10.3969/j.issn.0372-2112.2016)
161.	Kazuyuki Matsumoto, Minoru Yoshida, Seiji Tsuchiya, Kenji Kita and Fuji Ren : Slang Analysis Based on Variant Information Extraction Focusing on the Time Series Topics, International Journal of Advanced Intelligence (IJAI), Vol.8, No.1, 84-98, 2016. (Summary) Recently, with increase of the number of users of Social Networking Sites, online communications have been more and more actively made, raising the possibility to use the big data on SNS for analyzing the diversity of language. Japanese language uses varieties of character types and such character types are combined and used for creating words and phrases. Therefore, it is difficult to morphologically analyze such words and phrases even though morphological analysis is a basic processing in natural language processing. Such words and phrases that are not registered in morphological analysis dictionaries are usually not defined strictly and semantic interpret for them seems to vary depending on deindividual. In this study, we chronologically analyze the topics related to slang on Twitter. In this paper, as a validation experiment, we conducted a topic analysis experiment chronogically by using the sequential tweet data, and discussed the difference of topic change according to the slang types. (Keyword) Slang / Topic analysis / Time-series analkysis (Tokushima University Institutional Repository) ● Metadata: 113910 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1571698602718115840 (Tokushima University Institutional Repository: 113910, CiNii: 1571698602718115840)
162.	Changqin Quan and Fuji Ren : Textual Emotion Recognition for Enhancing Enterprise Computing, Enterprise Information Systems, Vol.10, No.4, 422-443, 2016. (Summary) The growing interest in affective computing (AC) brings a lot of valuable research topics that can meet different application demands in enterprise systems. The present study explores a sub area of AC techniques textual emotion recognition for enhancing enterprise computing. Multi-label emotion recognition in text is able to provide a more comprehensive understanding of emotions than single label emotion recognition. A representation of emotion state in text is proposed to encompass the multidimensional emotions in text. It ensures the description in a formal way of the configurations of basic emotions as well as of the relations between them. Our method allows recognition of the emotions for the words bear indirect emotions, emotion ambiguity and multiple emotions. We further investigate the effect of word order for emotional expression by comparing the performances of bag-of-words model and sequence model for multi-label sentence emotion recognition. The experiments show that the classification results under sequence model are better than under bag-of-words model. And homogeneous Markov model showed promising results of multi-label sentence emotion recognition. This emotion recognition system is able to provide a convenient way to acquire valuable emotion information and to improve enterprise competitive ability in many aspects. (Link to Publication Site) ● Publication site (DOI): 10.1080/17517575.2014.948935 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84956754901 (DOI: 10.1080/17517575.2014.948935, Elsevier: Scopus)
163.	Lei Wang, Fuji Ren and Duoqian Miao : Multi-Label Emotion Recognition of Weblog Sentence Based on Bayesian Networks, IEEJ Transactions on Electrical and Electronic Engineering (TEEE), Vol.11, No.2, 178-184, 2016. (Summary) An increasing number of common users, in the Internet age, tend to express their emotions on the Web about everything they like or dislike. As a consequence, the number of all kinds of reviews, such as weblogs, production reviews, and news reviews, grows rapidly. This makes it difficult for people to understand the opinions of the reviews and obtain useful emotion information from such a huge number of reviews. Many scientists and researchers have attached more attention to emotion analysis of online information in the natural language processing field. Different from previous works, which just focused on the single-label emotion analysis, this paper takes into account rich and delicate emotions and gives special regard to multi-label emotion recognition for weblog sentences based on the Chinese emotion corpus (Ren-CECps). Using the theory of Bayesian networks and probabilistic graphical model, the latent emotion variable and topic variable are employed to find out the complex emotions of weblog sentences. Our experimental results on the multi-label emotion topic model demonstrate the effectiveness of the model in recognizing the polarity of sentence emotions. (Keyword) latent Dirichlet allocation / multi-label classification / emotion recognition / Gibbs sampling (Link to Publication Site) ● Publication site (DOI): 10.1002/tee.22204 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1002/tee.22204 (DOI: 10.1002/tee.22204)
164.	Xiaohua Wang, Wei Huang, Chao Jin, Min Hu and Fuji Ren : Facial Expression Recognition Based on the Optimal Matching of Multi-feature and Multi-classifier, Opto-Electronic Engineering, Vol.43, No.3, 73-79, 2016. (Keyword) facial expression recognition / Principal Component Analysis / optimal integration of multiple classifiers / adaptive decision (Link to Publication Site) ● Publication site (DOI): 10.3969/j.issn.1003-501x.2016.03.012 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.3969/j.issn.1003-501x.2016.03.012 (DOI: 10.3969/j.issn.1003-501x.2016.03.012)
165.	Bin Zhang, Changqin Quan and Fuji Ren : Overview of Speech Synthesis in Development and Methods, Journal of Chinese Computer Systems, Vol.37, No.1, 186-192, 2016. (Summary) In human computer interaction the most natural and the best way to exchange is the communication by human voice.Which is mainly related to speech synthesis that is the technology of converting text to speech.This paper provides a concise but deep introduction to the development of speech synthesis and propose the problems and solutions in the development of speech synthesis.The researchers who are just entering the field of speech synthesis can stand on the shoulders of giants and have a clear and deep understanding of voice synthesis and start working with a correct judgment.In this paper first the effective methods which are already exist and mainstream in speech synthesis are overall introduced and the main idea of these methods as well as their advantages and disadvantages are described.On this basis we inspire new ideas.After that this paper illustrates the efforts respectively at home and abroad in recent years that researchers have done in the field of speech synthesis.Then objective evaluate and analyze gains and losses in synthesis technology improvements and draw the trend of synthesis technology in recent years.Finally get the prospect in speech synthesis pointing the bottleneck in development and trying to give direction to solve them. (Keyword) speech synthesis / HTS / text analysis / HCI
166.	Changqin Quan and Fuji Ren : Weighted high-order hidden Markov models for compound emotions recognition in text, Information Sciences, Vol.329, 581-596, 2016. (Summary) Emotion recognition in text has attracted a great deal of attention recently due to many practical applications and challenging research problems. In this paper, we explore an efficient identification of compound emotions in sentences using hidden Markov models (HMMs). In this problem, emotion has temporal structure and can be encoded as a sequence of spectral vectors spanning an article range. The major contributions of the research include the (i) proposal of weighted high-order HMMs to determine the most likely sequence of sentence emotions in an article. The weighted high-order HMMs take into account the impact degree of context emotions with different lengths of history; (ii) introduction of a representation of compound emotions by a sequence of binary digits, namely emotion code; (iii) development of an architecture that uses the emotions of simple sentences as part of known states in the weighted high-order hidden Markov emotion models for further recognizing more unknown sentence emotions. The experimental results show that the proposed weighted high-order HMMs is quite powerful in identifying sentence emotions compared with several state-of-the-art machine learning algorithms and the standard n-order hidden Markov emotion models. And the use of emotion of simple sentences as part of known states is able to improve the performance of the weighted n-order hidden Markov emotion models significantly. (Keyword) Affective computing / Compound emotions / Sentence emotion recognition / Hidden Markov models / Weighted n-order (Link to Publication Site) ● Publication site (DOI): 10.1016/j.ins.2015.09.050 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84949633818 (DOI: 10.1016/j.ins.2015.09.050, Elsevier: Scopus)
167.	Fuji Ren and Haitao Yu : Role-explicit query extraction and utilization for quantifying user intents, Information Sciences, Vol.329, No.1, 568-580, 2016. (Summary) In this study, we focus on how to extract role-explicit queries from a Chinese query log. A framework that performs role-explicit query extraction concurrently with intent role annotation is proposed. Instead of independently processing each query, the human wisdom hidden in mul-sessions is deployed to quantify the certainty of a word being the kernel-object. A sliding-window algorithm is proposed to extract role-explicit queries per mul-session. To filter the unreliable results produced by this algorithm, a pattern-based algorithm that performs a global purification is designed. The entire framework enables us to obtain a repository of sufficient role-explicit queries from a query log without human intervention. We also investigate the usefulness of aggregative role-explicit query extraction. Based a repository of role-explicit queries, we derive the richness value to quantify the richness of kernel-object oriented intents. An experimental application of the proposed framework for role-explicit query extraction to the query log SogouQ shows that: it achieves satisfactory performance. Furthermore, the richness value provides a way to capture underspecified and/or ambiguous queries, which allows selective operations to be performed depending on the nature of the queries. (Keyword) Kernel-object / Modifier / Richness value / Query extraction (Link to Publication Site) ● Publication site (DOI): 10.1016/j.ins.2015.09.052 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84949644900 (DOI: 10.1016/j.ins.2015.09.052, Elsevier: Scopus)
168.	XIN KANG, Fuji Ren and Yunong Wu : Semi-Supervised Learning of Author-Specific Emotions in Micro-Blogs, IEEJ Transactions on Electrical and Electronic Engineering (TEEE), Vol.11, No.6, 768-775, 2016. (Summary) Learning emotions from texts has been an active research topic in affective computing. However, the lack of reliable connection between emotions and language features has caused severely biased emotion predictions. Moreover, the author-specific patterns in emotion expression could potentially affect emotion predictions, which has never been studied. In this paper, we propose a semisupervised learning algorithm to learn emotional features from large-scaled micro-blog documents with a Bayesian network, and introduce an emotion transition factor to generate the author-specific emotion predictions. We infer the author-specific emotions in micro-blog streams through belief propagation, and learn the emotional features through an expectation maximization estimation procedure. We report results of single-label and multilabel emotion predictions on a micro-blog stream corpus, and analyze the improvements achieved by the semisupervised feature learning strategy and the incorporation of emotion transition patterns. Finally, we perform personality analysis based on the authors' emotion distribution and examine emotion distributions in the learned features. (Link to Publication Site) ● Publication site (DOI): 10.1002/tee.22302 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1002/tee.22302 (DOI: 10.1002/tee.22302)
169.	Fuji Ren and Zhong Huang : Facial expression recognition based on AAM-SIFT and adaptive regional weighting, IEEJ Transactions on Electrical and Electronic Engineering (TEEE), Vol.10, No.6, 713-722, 2015. (Summary) The active appearance model (AAM), one of the most effective facial feature localization methods, is widely used in frontal facial expression recognition. However, non-frontal facial expression recognition is important in many scenarios. Thus, we propose a new method for facial expression recognition based on AAM-SIFT and adaptive regional weighting. First, multi-pose AAM templates are used for pose estimation and feature point location of the facial expression image. For effective and efficient description of these feature points, a hybrid representation, which integrates gradient direction histograms based on the descriptors of scale-invariant feature transform (SIFT) and AAM, is utilized to form AAM-SIFT features. Meanwhile, according to different expression regions, AAM-SIFT features are divided into different groups and the obtained adaptive weights by means of a regional weighted method based on the fuzzy C-means (FCM) clustering algorithm. Finally, the membership degree computed by FCM, which represents the possibility for each class, is regarded as the input feature vector for support vector machine (SVM) classifier. Extensive experiments on BU-3DFE database with six facial expressions and seven poses demonstrate the effectiveness of different types of weighting strategies and the influence of different features. Comparison with other state-of-art methods illustrates that the proposed method not only improves the recognition rates of the frontal face but also has better robustness for non-frontal facial expressions. (Keyword) appearance model / gradient direction histogram / scale-invariant feature transform / fuzzy c-means clustering / non-frontal facial image (Link to Publication Site) ● Publication site (DOI): 10.1002/tee.22151 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1002/tee.22151 (DOI: 10.1002/tee.22151)
170.	Tian Chen, Xin Yi, Liuyang Zheng, Wei Wang, Huaguo Liang, Fuji Ren and Jun Liu : Low Power Deterministic Test Scheme based on Viterbi, Journal of Compter-Aided Design & Computer Graphics, Vol.28, No.5, 821-829, 2015. (Keyword) low power test / test data compression / block compatible encoding / Viterbi algorithm (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84973394929 (Elsevier: Scopus)
171.	Yan Sun, Changqin Quan, XIN KANG, Zuopeng Zhang and Fuji Ren : Customer emotion detection by emotion expression analysis on adverbs, Information Technology and Management, Vol.16, No.4, 303-311, 2015. (Summary) The growing interests of affective computing(AC) and its implementation in e-business demandresearchers to explore the applications of AC techniques indetecting customer emotions. Recent studies have shownthat language is powerful in conveying emotions, and agood understanding of major language features bears greatimplications for customer relationship management.However, the effect of adverbs in text emotion predictionhas only been briefly mentioned in a few related works, butnever thoroughly studied. This paper addresses the gap byinvestigating how to detect customer emotions throughanalyzing the adverbs in emotion expressions. In particular,we develop a Japanese adverb emotion corpus, analyzeemotion usage of adverbs, and further derive an adverbemotionlexicon and its rule base. Utilizing these resources,we design and perform experiments to classify emotions in sentences so as to evaluate the effectiveness of differentadverb features including adverbs, adverb emotions, andadverb emotion rules. Our experiments and analysis showthe great impact of adverbs on emotion expressions, whichcan be applied to assist e-businesses in improving customerrelated processes. (Keyword) Affective computing / E-business / Customer emotions / Adverb analysis (Link to Publication Site) ● Publication site (DOI): 10.1007/s10799-014-0204-2 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1007/s10799-014-0204-2 (DOI: 10.1007/s10799-014-0204-2)
172.	Lianghu Quan, Yu Gu, Mengni Chen and Fuji Ren : Research on pasive human activity recognition using WiFi ambient signals, Journal of University of Scinece and Technology of China, Vol.45, No.4, 308-313, 2015. (Summary) Although traditional k-nearest neighbor(K-NN) and bagging can recognize effectively less human activities using WiFi ambient signal, recognizing seven activities, namely, empty, walking, sitting, standing, sleeping, fallen and running, is not ideal. To further improve the performance, a new algorithm named fusion algorithm has been designed. It significantly outperform K-NN and bagging in terms of the recognition ratio in both single-subject and multi-subject experiments. (Keyword) WiFi ambient signals / Human activities / Fusion algorithm / Multi-subject / forecast (Link to Publication Site) ● Publication site (DOI): 10.3969/j.issn.0253-2778.2015.04.008 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84986227114 (DOI: 10.3969/j.issn.0253-2778.2015.04.008, Elsevier: Scopus)
173.	Yanqiu Li, Fuji Ren, Liangfeng Xu, Min HU and Zixi Yu : Face Recognition Based on ULBP and BP Neural Network, International Journal of Advanced Intelligence (IJAI), Vol.7, No.1, 103-114, 2015. (Summary) Face recognition is a research hotspot in computer vision field. Compared with the traditional feature extraction algorithms, Local Binary Pattern has many advantages, such as high accuracy, fine, light illumination invariance, etc., so it is widely used to extract facial texture feature. Firstly, we put the image evenly into blocks and constructed sub-image sets. This would be more efficient to extract feature data. Through combining with BP neural network, we make use of decision fusion and weighted fusion two ways to obtain the classification results of unknown samples. Experimental results on ORL face database show that this method is effective. (Keyword) LBP / BP neural network / fusion / face recognition
174.	Min Hu, Xiaoyin Huang, Fuji Ren and Xiaohua Wang : Facial Expression Recognition Based on MBP and Sparse Representation, International Journal of Advanced Intelligence (IJAI), Vol.7, No.1, 95-102, 2015. (Summary) Recently, sparse representation attracts widespread attention in the field of pattern recognition and artificial intelligence. Gabor features based sparse representation classifier had been introduced in face recognition research field and achieved good recognition effect. But its enormous time cost and space cost and computational complexity in the real system cannot be ignored. So this paper proposed a novel facial expression recognition method based on monogenic binary pattern and sparse representation. The proposed method extracts features from the facial expression image by using monogenic binary pattern and utilizes information entropy to weight the feature block, then constructs sparse dictionary and makes use of residual value for classification. Our proposed method was tested on the popular FERET and Cohn-Kanade facial database and obtained the average rates 94.92% and 97.46% respectively. The experimental results show that the sparse dictionary which is constructed by the proposed features has stronger ability for sparse representation and has better performance in time and space efficiency. (Keyword) Monogenic binary pattern / Information entropy / Sparse representation / Facial expression.
175.	Jiaqi Ye, Xiao Sun, Fuji Ren and Fang Tian : Social Network Influenza Epidemic Detection Based on SVM and CRF, International Journal of Advanced Intelligence (IJAI), Vol.7, No.1, 66-79, 2015. (Summary) Influenza is an acute respiratory illness and widespread activity that occurs every year. Detection and prevention of Influenza in its earliest stage would reduce the spread range of the illness. Sina microblog is a popular micro blogging service in China, which could provide perfect reference sources for flu detection due to its real-time characteristic and large number of active users posting about their daily life continually. In this paper, we investigate the real-time flu detection problem and propose a flu detection model with emotion factors and semantic information (Em-Flu model). First, we extract flu-related microblog posts automatically in real-time using a simple SVM filter. We use association rule mining to extract strongly associated features as additional features of posts to overcome the limitation of 140 words for posts, including sentimental analysis information which can help to classify the posts without features. Then Conditional Random Field model is revised and applied to detect the transition time of flu that we can find out which place is more likely for influenza outbreak and when an influenza outbreak is more likely in a particular city or province in China. The experimental results display when and where influenza epidemic is more likely to occur and show the robustness and effectiveness of the proposed model might help health organizations in predicting a flu outbreak allowing them to take appropriate action in a timely manner. (Keyword) Influenza Detection / Conditional Random Field; / transition time detection / Social media mining / Public health
176.	Xiaohua Wang, Dengyong Hou, Min Hu and Fuji Ren : Dual-modality emotion recognition of facial expressions and gestures, International Journal of Advanced Intelligence (IJAI), Vol.7, No.1, 24-34, 2015. (Summary) We carry out a research of dual-modality emotion recognition about facial expressions and gestures and then propose a method combined facial expressions and gestures for dual-modality emotion recognition. Firstly, we obtain the expression image and gesture image by pre-processed the hand-over-face image. The pretreatment included reconstruct facial expression image through PCA algorithm. Secondly, we extract the LBP features from expression image and the Hu moment invariant features and Fourier descriptor features from gesture image. We use SVM and KNN to coarse classification recognition the expression features and gesture features respectively. Finally, we mix classification results of facial expressions and gestures together by using the linear weighted voting algorithm proposed in this paper. The experimental results show that this method has the better discrimination in the dual-modality emotional database established by ourselves. (Keyword) Facial expression / Gesture / Dual-modality emotion recognition / Decision level fusion
177.	Min Hu, Yihong Cheng, Xiaohua Wang, Fuji Ren, Liangfeng Xu and Xiaoyin Huang : Facial Expression Recognition Based on asymmrtric region local gradient coding, Journal of Image and Graphics, Vol.20, No.10, 1313-1321, 2015. (Summary) 顔表情認識は近年盛んに研究されてきたが，多くの問題点が残されている．本稿では，非対称領域局所勾配符号化に基づく表情認識手法を提案する．提案した手法に基づき実験システムを構築し，様々な実験を行なった．実験結果から，提案した手法の有効性を確かめることができた． (Link to Publication Site) ● Publication site (DOI): 10.11834/jig.20151004 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.11834/jig.20151004 (DOI: 10.11834/jig.20151004)
178.	Xiao Sun, Chongyuan Sun and Fuji Ren : New Word Detection and Emotional Tendency Judgment Based on Deep Structured Model, Computer Science, Vol.42, No.9, 208-213, 2015. (Summary) With the development of social network,new words appear ceaselessly.The appearance of new word tends to characterize the social hot spot or represent certain public mood.The new word detection and emotional tendency judgment provide a new way for the public mood forecast.We constructed the deep conditional random fields model for the sequence labeling,introduced part of speech,character position,the ability of word formation as features,and combined it with the crowd sourcing network dictionary and the other third party dictionary.Traditional method based on emotional dictionary is difficult to judge the new word emotional tendency.We expressed word as a vector of K dimension based on neural network language model in order to find the nearest words to the new word in the vector space.According to the emotional tendency of these words and the distance between them and the new word,the new word sentiment is judged.The experiment on corpus of Peking university demonstrates the feasibility of the proposed model and method,in which the new word detection F-value is 0.991,and the emotion recognition accuracy is 70%. (Link to Publication Site) ● Publication site (DOI): 10.11896/j.issn.1002-137X.2015.09.040 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.11896/j.issn.1002-137X.2015.09.040 (DOI: 10.11896/j.issn.1002-137X.2015.09.040)
179.	Yiming Tang and Fuji Ren : Variable differently implicational algorithm of fuzzy inference, Journal of Intelligent and Fuzzy Systems, Vol.28, No.4, 1885-1897, 2015. (Summary) To reveal the inherent essence of current differently implicational algorithms for fuzzy inference, the variable differently implicational algorithm is put forward and investigated. The differently implicational principles are improved from variable and generalized viewpoint. Furthermore, focusing on the FMP (fuzzy modus ponens) problem, unified forms of the new algorithm are obtained for R-implications and S-implications. Following that, the optimal differently implicational solutions are achieved for several specific R-implications and S-implications. Lastly, the new algorithm makes the current differently implicational algorithms compose a united whole. (Keyword) Fuzzy inference / fuzzy modus ponens / fuzzy implication / compositional rule of inference / fully implicational algorithm (Link to Publication Site) ● Publication site (DOI): 10.3233/IFS-141476 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84924598706 (DOI: 10.3233/IFS-141476, Elsevier: Scopus)
180.	Ye Wu and Fuji Ren : Exploiting Opinion Distribution for Topic Recommendation in Twitter, IEEJ Transactions on Electrical and Electronic Engineering (TEEE), Vol.10, No.5, 567-575, 2015. (Summary) The popular social networking service Twitter provides rapidly updated information and online trends, which enriches andbenefits peoples daily life. At the same time, how to find out the really interesting and relevant topics from the massivestreams of tweets, to provide precise topic recommendation for users, becomes a challenging problem in the real world. Previouscollaborative filtering methods give solutions to traditional recommendation tasks considering users positive reviews to helprecommend items. However, to the problem what is interesting to whom in Twitter, positive opinions toward a topic do notimply that the user will be interested in it with high probability, for the user probably prefers to know those controversial topicsor hot events with a large number of negative posts. In this paper, we exploit the characteristics of topical opinion distributionfor improving the performance of recommendation. The experimental results on a real-world Twitter dataset show that theproposed opinion-distribution-aware topic recommendation (ODA-TR) approach outperforms the state-of-the-art collaborativerecommendation methods (Keyword) collaborative filtering / opinion distribution / topic recommendation / Twitter (Link to Publication Site) ● Publication site (DOI): 10.1002/tee.22120 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84937731417 (DOI: 10.1002/tee.22120, Elsevier: Scopus)
181.	Fuji Ren and Kazuyuki Matsumoto : Semi-automatic Creation of Youth Slang Corpus and Its Application to Affective Computing, IEEE Transactions on Affective Computing, Vol.7, No.2, 176-189, 2015. (Summary) This paper proposes a method to semi-automatically construct a corpus that includes Japanese youth slang called Wakamono Kotoba. The process of semi-automatic corpus construction is composed of the first step is automatic collection of example sentence, the second step is tag annotation to collected sentences, and the final step is manually modifying tag and noise reduction. In this process, there are two problems. The first problem is quality of the automatic collected corpora. The second is the accuracy of tag annotation. If the automatically annotated tags are unreliable, after all, it takes long time to modify them manually. As a solution of the first problem, we proposed a filtering method to remove meaningless sentences (noise sentences) automatically. In order to solve a second problem, we proposed an emotion estimation method that can be applied to the sentences that included youth slang and were difficult to be analyzed automatically. The result of the accuracy evaluation showed improvement in F1-Score compared to the machine learning method and confirms the effectiveness of the proposed method. (Keyword) Emotion corpus / semi-automatic corpus construction / Affective Computing / youth slang / Wakamono Kotoba (Link to Publication Site) ● Publication site (DOI): 10.1109/TAFFC.2015.2457915 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84973495084 (DOI: 10.1109/TAFFC.2015.2457915, Elsevier: Scopus)
182.	Fuji Ren, XIN KANG and Changqin Quan : Examining Accumulated Emotional Traits in Suicide Blogs with an Emotion Topic Model, IEEE Journal of Biomedical and Health Informatics, Vol.20, No.5, 1384-1396, 2015. (Summary) Suicide has been a major cause of death throughout the world. Recent studies have proved a reliable connection between the emotional traits and suicide. However, detection and prevention of suicide are mostly carried out in the clinical centers, which limits the effective treatments to a restricted group of people. To assist detecting suicide risks among the public, we propose a novel method by exploring the accumulated emotional information from people's daily writings (i.e. Blogs), and examining these emotional traits which are predictive of suicidal behaviors. A complex emotion topic (CET) model is employed to detect the underlying emotions and emotion-related topics in the Blog streams, based on eight basic emotion categories and five levels of emotion intensities. Since suicide is caused through an accumulative process, we propose three accumulative emotional traits, i.e., accumulation, covariance, and transition of the consecutive Blog emotions, and employ a generalized linear regression algorithm to examine the relationship between emotional traits and suicide risk. Our experiment results suggest that the emotion transition trait turns to be more discriminative of the suicide risk, and that the combination of three traits in linear regression would generate even more discriminative predictions. A classification of the suicide and non-suicide Blog articles in our additional experiment verifies this result. Finally, we conduct a case study of the most commonly mentioned emotion-related topics in the suicidal Blogs, to further understand the association between emotions and thoughts for these authors. (Tokushima University Institutional Repository) ● Metadata: 118262 (Link to Publication Site) ● Publication site (DOI): 10.1109/JBHI.2015.2459683 (Link to Search Site for Scientific Articles) ● PubMed @ National Institutes of Health, US National Library of Medicine (PMID): 26208372 ● Search Scopus @ Elsevier (PMID): 26208372 ● Search Scopus @ Elsevier (DOI): 10.1109/JBHI.2015.2459683 (Tokushima University Institutional Repository: 118262, DOI: 10.1109/JBHI.2015.2459683, PubMed: 26208372)
183.	Min Hu, Kun Li, Xiaohua Eang and Fuji Ren : Facial expression recognition based on histogram weighted HCBP, Journal of Electronic Measurement and Instrumentation, Vol.29, No.7, 953-960, 2015. (Summary) In order to overcome the limitation of local binary pattern ( LBP) and its improved algorithm a facial expression method based on histogram weighted HCBP is proposed Firstly facial image is divided into some uniform sub-image and HCBP operator is used to extract texture feature Then the information entropy is used to calculate the weight of every sub-image weighted HCBP histogram of sub-image is combined with the HCBP histogram of the original image and the result histogram image is accomplished as the facial expression feature Finally the expression is classified with the nearest neighbor classifier Using the combination of Haar-like feature and CBP operator makes the description of local feature more sufficient The introduction of information entropy can distinguish the contribution of different partitions of the face The experimental results in JAFFE library and Cohn-Kanade library show that the HCBP method outperforms than existing LBP methods in both the recognition rate and the speed (Keyword) LBP / HCBP / facial expression recognition / histogram weighted (Link to Publication Site) ● Publication site (DOI): 10.13382/j.jemi.2015.07.003 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.13382/j.jemi.2015.07.003 (DOI: 10.13382/j.jemi.2015.07.003)
184.	Bin Zhang, Fuji Ren and Changqin Quan : Overview of Speech Synthesis in Development and Methods, Journal of Chinese Computer Systems, Vol.36, No.6, 1-8, 2015. (Summary) Spoken dialogue system is the core technology in the field of human-computer interaction, and it is an important way to realize the harmonious human-computer interaction, the research has great theory significance and application value. The advances of theory and technology in spoken dialogue systems have always been greatly concerned. The status and advances of dialogue management and spoken dialogue system are comprehensively summarized in this paper. First, the main research questions of spoken dialogue system are introduced comprehensively, including the research contents of the modules, key technologies, portability and robust design. Then, the various spoken dialogue management strategies are systematically analyzed from the perspective of theoretical models, advances and usability. Finally, several possible directions and problems for further consideration and discussion are also mentioned.
185.	Yu Gu and Fuji Ren : Energy-efficient Indoor Localization of Smart Hand-held Devices Using Bluetooth, IEEE Access, Vol.3, 1450-1461, 2015. (Summary) Indoor localization of smart hand-held devices is essential for location based services of pervasive applications. Previous research mainly focuses on exploring wireless signal fingerprints for this purpose, and several shortcomings need to be addressed first before real-world usage, e.g., demanding a large number of APs or labor-intensive site survey. In this paper, through a systematic empirical study, we first gain in-depth understandings of Bluetooth characteristics, i.e., the impact of various factors such as distance, orientation, and obstacles on the Bluetooth RSSI (Received Signal Strength Indicator). Then, by mining from historical data, a novel localization model is built to describe the relationship between RSSI and the device location. On this basis, we present an energy- efficient indoor localization scheme that leverages user motions to iteratively shrink the search space to locate the target device. MLDB has been prototyped and evaluated in several real-world scenarios. Extensive experiments show that our algorithm is efficient in terms of localization accuracy, searching time and energy consumption. (Keyword) Energy efficiency / indoor Localization; / Data Mining / Bluetooth / IoT (Link to Publication Site) ● Publication site (DOI): 10.1109/ACCESS.2015.2441694 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84961068421 (DOI: 10.1109/ACCESS.2015.2441694, Elsevier: Scopus)
186.	Fuji Ren, Mengni Chen and Yu Gu : WeWatch: An Application for Watching Video Across Two Mobile Devices, ZTE COMMUNICATIONS, Vol.13, No.2, 17-22, 2015. (Summary) In recent years, high resolution video has developed rapidly and widescreen smart devices have become popular. We present an Android application called WeWatch that enables high resolution video to be shared across two mobile devices when they are close to each other. This concept has its inspiration in machine to machine connections in the Internet of Things (loT). We ensure that the two parts of the video are the same size over both screens and are synchronous. Further, a user can play, pause, or stop the video by moving one device a certain distance from the other. We decide on appropriate distances through experimentation. We implemented WeWatch on Android operating system and then optimize Watch so battery consumption is reduced. The user ex perience provided by WeWatch was evaluated by students through a questionnaire, and the reviews indicated that WeWatch does improve the viewing experience. (Keyword) together watching experience / screen adaptation / internet of things / distance estimation / energy efficiency (Link to Publication Site) ● Publication site (DOI): 10.3969/j.issn.16735188.2015.02.004 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.3969/j.issn.16735188.2015.02.004 (DOI: 10.3969/j.issn.16735188.2015.02.004)
187.	Jun Liu, Qingqing Qian, Xi Wu, Wei Wang, Tian Chen and Fuji Ren : Optimizing pre-bond and post-bond test time for three dimension IP Cores, Computer Engineering and Applications, Vol.19, No.11, 1-7, 2015. (Link to Publication Site) ● Publication site (DOI): 10.3778/j.issn.1002-8331.1412-0164 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.3778/j.issn.1002-8331.1412-0164 (DOI: 10.3778/j.issn.1002-8331.1412-0164)
188.	Fuji Ren, Yu Wang and Changqin Quan : TFSM-based dialogue management model framework for affective dialogue systems, IEEJ Transactions on Electrical and Electronic Engineering (TEEE), 1-7, 2015. (Summary) A new dialogue management model for affective dialogue system, which aims to provide a service of information inquiry and affective interaction, is proposed in this paper. First, we construct two finite state machines (TFSM) to model the user and the system, respectively, and simulate the dialogue process as an information exchange between the two state machines. All possible state transitions in dialogue and its probabilities of the user are summarized as a user model, which is helpful for the system to inference and predict the user's internal states. Second, we further discuss the implementation methods of information inquiry and emotional response modules. Finally, we employ the return function of partially observable Markov decision processes (POMDP) model to analyze and evaluate the TFSM-based dialogue management model. The experimental results not only show the relationships between the average returns, recognition error rates, and state transition probabilities but also confirm that our TFSM-based dialogue management model outperforms the conventional FSM model. (Keyword) dialogue management model / affective dialogue system / finite state machine / affective computing (Link to Publication Site) ● Publication site (DOI): 10.1002/tee.22100 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84931572981 (DOI: 10.1002/tee.22100, Elsevier: Scopus)
189.	Min Hu, Jiang Hr, Xiaohua Wang, Hongbo Chen, Kun Li and Fuji Ren : Precise local feature description for facial expression recognition, Journal of Image and Graphics, Vol.19, No.11, 1613-1622, 2015. (Keyword) acial expression recognition / precise local features / sufficient vector triangle / a variety of scales (Link to Publication Site) ● Publication site (DOI): 10.11834/jig.20141109 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.11834/jig.20141109 (DOI: 10.11834/jig.20141109)
190.	Yu Gu, Fuji Ren, Yusheng JI and Ji Li : The Evolution of Sink Mobility Management in Wireless Sensor Networks: A Survey, IEEE Communications Surveys and Tutorials, 1-19, 2015. (Summary) Sink mobility has long been recognized as an efficient method of improving system performance in wireless sensor networks (WSNs), e.g. relieving traffic burden from a specific set of nodes. Though tremendous research efforts have been devoted to this topic during the last decades, yet little attention has been paid for the research summarization and guidance. This paper aims to fill in the blank and presents an up-to-date survey on the sink mobility issue. Its main contribution is to review mobility management schemes from an evolutionary point of view. The related schemes have been divided into four categories: uncontrollable mobility (UMM), pathrestricted mobility (PRM), location-restricted mobility (LRM) and unrestricted mobility (URM). Several representative solutions are described following the proposed taxonomy. To help readers comprehend the development flow within the category, the relationship among different solutions is outlined, with detailed descriptions as well as in-depth analysis. In this way, besides some potential extensions based on current research, we are able to identify several open issues that receive little attention or remain unexplored so far. (Keyword) Wireless sensor networks / energy efficiency / mobility management / sink mobility (Link to Publication Site) ● Publication site (DOI): 10.1109/COMST.2015.2388779 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/COMST.2015.2388779 (DOI: 10.1109/COMST.2015.2388779)
191.	Changqin Quan and Fuji Ren : Feature-level sentiment analysis by using comparative domain corpora, Enterprise Information Systems, 1-18, 2014. (Summary) Feature-level sentiment analysis (SA) is able to provide more fine-grained SA oncertain opinion targets and has a wider range of applications on E-business. Thisstudy proposes an approach based on comparative domain corpora for feature-levelSA. The proposed approach makes use of word associations for domain-specificfeature extraction. First, we assign a similarity score for each candidate feature todenote its similarity extent to a domain. Then we identify domain features based ontheir similarity scores on different comparative domain corpora. After that, dependencygrammar and a general sentiment lexicon are applied to extract and expand feature orientedopinion words. Lastly, the semantic orientation of a domain-specific feature isdetermined based on the feature-oriented opinion lexicons. In evaluation, we comparethe proposed method with several state-of-the-art methods (including unsupervised andsemi-supervised) using a standard product review test collection. The experimentalresults demonstrate the effectiveness of using comparative domain corpora. (Keyword) affective computing / affective computing / frequencyinverse document frequency / pointwise mutual information / pointwise mutual information (Link to Publication Site) ● Publication site (DOI): 10.1080/17517575.2014.985613 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1080/17517575.2014.985613 (DOI: 10.1080/17517575.2014.985613)
192.	Jun Liu, Xi Wu, Huaguo Liang and Fuji Ren : Optimizing the number of leaf nodes and TSVs in three dimensional scan tree, SCIENTIA SINICA Informationis, Vol.44, No.1, 1-13, 2014. (Summary) Scan tree architecture can effectively reduce test data volume, test time and test cost for integratedcircuits. To reduce the number of leaf nodes and TSVs(through silicon vias) in scan tree for three dimensionalintegrated circuits, this paper firstly draws the conclusion that the minimum number of leaf nodes is the numberof scan cells contained in the maximal compatible group. Then, the necessary and sufficient condition achievingthe minimum number of leaf nodes is presented. On the basis above, a heuristic algorithm is proposed, whichcan minimize the number of leaf nodes and reduce consumed TSVs as many as possible. Experimental resultsdemonstrate the effectiveness of the proposed technique. (Link to Publication Site) ● Publication site (DOI): 10.1360/N112014-00133 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1360/N112014-00133 (DOI: 10.1360/N112014-00133)
193.	Changqin Quan and Fuji Ren : Visualizing Emotions from Chinese Blogs by Textual Emotion Analysis and Recognition Techniques, International Journal of Information Technology & Decision Making, Vol.13, 1-20, 2014. (Summary) The research on blog emotion analysis and recognition has become increasingly important in recent years. In this study, based on the Chinese blog emotion corpus (Ren-CECps), we analyze and compare blog emotion visualization from different text levels: word, sentence, and paragraph. Then, a blog emotion visualization system is designed for practical applications. Machine learning methods are applied for the implementation of blog emotion recognition at different textual levels. Based on the emotion recognition engine, the blog emotion visualization interface is designed to provide a more intuitive display of emotions in blogs, which can detect emotion for bloggers, and capture emotional change rapidly. In addition, we evaluated the performance of sentence emotion recognition by comparing five classification algorithms under different schemas, which demonstrates the effectiveness of the Complement Naive Bayes model for sentence emotion recognition. The system can recognize multi-label emotions in blogs, which provides a richer and more detailed emotion expression. (Link to Publication Site) ● Publication site (DOI): 10.1142/S0219622014500710 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1142/S0219622014500710 (DOI: 10.1142/S0219622014500710)
194.	Jun Wang, Fuji Ren and Lei Li : Recognizing Sentiment of Relations between Entities in Text, IEEJ Transactions on Electrical and Electronic Engineering (TEEE), Vol.9, No.6, 614-620, 2014. (Summary) Recently, sentiment analysis for identifying positive or negative opinions from texts has received much attention. In this paper,we introduce sentiment analysis into a new field, which recognizes sentiment of relations between entities in the text. Threesentiment polarities between entities are recognized, namely positive, negative, and neutral. The difficulty in this work is thatseveral pairs of entities may appear in the same sentence, and their sentiment polarities are determined by different relatedregions of the sentence. In addition, different features of words and their interactions in a related region will affect the finalsentiment. It is difficult to process this using rigid rule-based methods. Therefore, we propose a machine-learning method basedon statistics. In the proposed method, the model of conditional random fields (CRFs) is used to annotate the sentiment polaritybetween entities with the help of the syntactic dependency tree. The string of words that connects two entities in the dependencytree is used as the related region to recognize the sentiment. Experimental results and comparison with the other methods basedon different principles and related regions suggest that the proposed method shows better performance and proves its validity.Moreover, the effect of different features on the CRF is word of the i th word in the sentence. We can get a CRF model using theCRF++ tool based on feature template and training corpus. After obtaining the model, sentiment of relations could be assignedautomatically. The algorithm is shown in Fig. 2. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley &Sons, Inc. (Keyword) role-explicit / intent role / kernel-object / modifier (Link to Publication Site) ● Publication site (DOI): 10.1002/tee.22017 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84907920235 (DOI: 10.1002/tee.22017, Elsevier: Scopus)
195.	Xiaohua Wang, Chao Jin, Fuji Ren and Min Hu : Research on facial expression recognition based on pyramid Weber local descriptor and the Dempster-Shafer theory of evidence, Journal of Image and Graphics, Vol.19, No.9, 1297-1305, 2014. (Summary) Feature extraction is the most critical step in pattern recognition, and facial expression recognition is no exception.Weber Local Descriptor (WLD) is a Method that can effectively extract texture information from images and has the advantages of being consistent with human perception of human beings and being insensitive to noise and non-monotonic illumination variations. However, WLD has some limitations in the feature representation of local details. To overcome these limitations, a facial expression recognition Method based on Pyramid WLD (PWLD) is proposed in this study.Method First, facial images are preprocessed. This step includes the detection of faces from facial expression databases and normalization. The salient regions of segment 2 that have significant contributions to facial expression recognition from images are also preprocessed. One of these salient regions is that which includes the eyes and eye brows, while another is that with the mouth. The sizes of salient regions differ, and these regions contain different information. Thus, we stratify these salient regions and divide each layer into different blocks. The PWLD features of each block in each layer are then extracted and cascaded to represent the global and local features of a salient region reasonably, with some parameter adjustments. Second, we compute for the Chi-square distance of the PWLD histograms in both the testing and training sets. We then choose the minimum distance in every category of expressionsand normalize this distance to construct the Basic Probability Assignment (BPA) as independent evidence. To create the BPA, we use curve fitting in numerical analysis by simulating several sets of data. Finally, fusion BPA is obtained by using the Dempster-Shafer rule, and the Results are further obtained by employing thedecision-making and judgment of Dempster-Shafertheory of evidence.Result By fusing the PWLD features of the two different salient regions with Dempster-Shafer theory of evidence, we can overcome the limitations of a single regional featureand acquire more reliable and accurate Results. We conduct some cross-validation experiments on the JAFFE and Cohn-Kanade facialexpression databases, and the average recognition rates reach up to 95.81% and 97.47%, respectively. In addition, we perform some experiments with other algorithms, such as LBP, LDP, and Gabor; we also conduct some comparative experiments that combine the PWLD with different classifiers, such as 1-NN and SVM.Conclusion The WLD, which is known as a robust image descriptor, can well extract the texture information of images. Moreover, the PWLD can accurately describe the local details, which have more advantages than the WLD features. The comparative Results of some typical Methodsverify the effectiveness and fault tolerance of the proposed Method. The proposed Method has certain robustness under simultaneous noise and light conditions. (Keyword) facial expression recognition / Weber local descriptor / pyramid Weber local descriptor / Dempster-Shafer(D-S) theory of evidence (Link to Publication Site) ● Publication site (DOI): 10.11834/jig.20140906 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.11834/jig.20140906 (DOI: 10.11834/jig.20140906)
196.	Changqin Quan, Meng Wang and Fuji Ren : An Unsupervised Text Mining Method for Relation Extraction from Biomedical Literature, PLoS ONE, Vol.9, No.7, e102039, 2014. (Summary) The wealth of interaction information provided in biomedical articles motivated the implementation of text mining approaches to automatically extract biomedical relations. This paper presents an unsupervised method based on pattern clustering and sentence parsing to deal with biomedical relation extraction. Pattern clustering algorithm is based on Polynomial Kernel method, which identifies interaction words from unlabeled data; these interaction words are then used in relation extraction between entity pairs. Dependency parsing and phrase structure parsing are combined for relation extraction. Based on the semi-supervised KNN algorithm, we extend the proposed unsupervised approach to a semi-supervised approach by combining pattern clustering, dependency parsing and phrase structure parsing rules. We evaluated the approaches on two different tasks: (1) Proteinprotein interactions extraction, and (2) Genesuicide association extraction. The evaluation of task (1) on the benchmark dataset (AImed corpus) showed that our proposed unsupervised approach outperformed three supervised methods. The three supervised methods are rule based, SVM based, and Kernel based separately. The proposed semi-supervised approach is superior to the existing semi-supervised methods. The evaluation on genesuicide association extraction on a smaller dataset from Genetic Association Database and a larger dataset from publicly available PubMed showed that the proposed unsupervised and semi-supervised methods achieved much higher F-scores than co-occurrence based method. (Link to Publication Site) ● Publication site (DOI): 10.1371/journal.pone.0102039 (Link to Search Site for Scientific Articles) ● PubMed @ National Institutes of Health, US National Library of Medicine (PMID): 25036529 ● Search Scopus @ Elsevier (PMID): 25036529 ● Search Scopus @ Elsevier (DOI): 10.1371/journal.pone.0102039 (DOI: 10.1371/journal.pone.0102039, PubMed: 25036529)
197.	Changqin Quan and Fuji Ren : Unsupervised Product Feature Extraction for Feature-oriented Opinion Determination, Information Sciences, Vol.272, 16-28, 2014. (Summary) Identifying product features from reviews is the fundamental step as well as a bottleneck in feature-level sentiment analysis. This study proposes a method of unsupervised product feature extraction for feature-oriented opinion determination. The domain-specific features are extracted by measuring the similarity distance of domain vectors. A domain vector is derived based on the association values between a feature and comparative domain corpora. A novel term similarity measure (PMITFIDF) is introduced to evaluate the association of candidate features and domain entities. The results show that our approach of feature extraction outperforms other state-of-the-art methods, and the only external resources used are comparative domain corpora. Therefore, it is generic and unsupervised. Compared with traditional pointwise mutual information (PMI), PMITFIDF showed better distinction ability. We also propose feature-oriented opinion determination based on feature-opinion pair extraction and feature-oriented opinion lexicon generation. The results demonstrate the effectiveness of our proposed method and indicate that feature-oriented opinion lexicons are superior to general opinion lexicons for feature-oriented opinion determination. (Link to Publication Site) ● Publication site (DOI): 10.1016/j.ins.2014.02.063 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84899473796 (DOI: 10.1016/j.ins.2014.02.063, Elsevier: Scopus)
198.	Misao Miyagawa, Tetsuya Tanioka, Yuko Yasuhara, Kazuyuki Matsumoto, Hirokazu Ito, Motoyuki Suzuki, Fuji Ren and Rozzano De Castro Locsin : Methodology for Developing a Nursing Administration Analysis System, Intelligent Information Management, Vol.6, No.3, 118-128, 2014. (Summary) Nursing administration requires a large volume of wide-ranging information, and nurse administrators are limited in their ability to compile and analyze information for nursing administration. The purpose of this study is to create methodology for developing a nursing administration analysis system to aid nurse administrators in performing outcome analysis. In this methodology, information required for nursing administration in the PSYCHOMS? (Psychiatric Outcome Management System, registered trademark) database is analyzed according to the individual needs of nurse administrators. It features a combination of a classification method and an extraction method for obtaining quantitative and qualitative data as information required for nursing administration, and enables nurse administrators to easily obtain analysis results that they directly need. This methodology converts the time required nurse administrators to collect and organize information into time for making considerations in order to devise strategies for improving the quality of nursing care services, and can improve the quality and efficiency of nursing administration. This may lead to an increase of the quality of nursing care services at psychiatric hospitals. This methodology is highly versatile as it can be applied in information management, not only for nursing, but for the entire psychiatric hospital. (Keyword) Nursing Administration / Clinical Pathways / analysis of variance / Analysis System / PSYCHOMS® (Link to Publication Site) ● Publication site (DOI): 10.4236/iim.2014.63013 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.4236/iim.2014.63013 (DOI: 10.4236/iim.2014.63013)
199.	Changqin Quan and Fuji Ren : Target Based Review Classification for Fine-Grained Sentiment Analysis, International Journal of Innovative Computing, Information and Control, Vol.10, No.1, 257-268, 2014. (Summary) Target based sentiment classification is able to provide more fine grained sentiment analysis. In this paper, we propose a similarity based approach for this problem. Firstly, a new measure of PMI-TFIDF by combining PMI (Pointwise mutual information) and TF-IDF (term frequencyinverse document frequency) is proposed to measure the association of words for extending related features for a given target. Then Polynomial Kernel (PK) method is applied to get the similarities between a review and the related features of different targets. The sentiment orientation of a review is determined by comparing their similarities with the target based opinion words. The comparisons between PMI and PMI-TFIDF showed that the extracted features that measured by PMI-TFIDF have closer association with the targets than the extracted features measured by PMI. And the association values measured by PMI-TFIDF showed better distinction between different features. The experiments also demonstrated the effectiveness and validation of the proposed approach on target based review classification, opinion words extraction, and target based sentiment classification. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84898628388 (Elsevier: Scopus)
200.	Haotao Yu and Fuji Ren : Automatic Role-explicit Query Extraction: A Divide-and-Conquer System Leveraging on Users' Reformulating Behaviors, IEEJ Transactions on Electrical and Electronic Engineering (TEEE), Vol.9, No.1, 62-70, 2014. (Summary) This paper presents a system that can automatically extract role-explicit queries from a query log without any human intervention. The key idea underlying our system is as follows: We perform a divide-and-conquer process through differentiating the sessions in a query log as mul-sessions and sin-sessions. According to the session type, different approaches are proposed. We translate the contextual information in mul-sessions as indirect human wisdom to facilitate role-explicit query extraction on mul-sessions. Furthermore, leveraging on the role-explicit queries extracted from mul-sessions, we learn the simplified word n-gram role model (SWNR) to facilitate role-explicit query extraction on sin-sessions. The experimental results show that our proposed system is clearly favored by the indirect human wisdom hidden in mul-sessions and achieves a satisfactory performance, namely more than 79% in terms of different metrics. (Keyword) role-explicit / intent role / kernel-object / modifier (Link to Publication Site) ● Publication site (DOI): 10.1002/tee.21937 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84889664165 (DOI: 10.1002/tee.21937, Elsevier: Scopus)
201.	Fuji Ren and Ye Wu : Predicting User-topic Opinions in Twitter with Social and Topical Context, IEEE Transactions on Affective Computing, Vol.4, No.4, 412-424, 2013. (Summary) With popular microblogging services like Twitter, users are able to share opinions towards hot topics online, in a more convenient way. The user generated data in Twitter is thus regarded as an opinion-rich resource, and has been exploited for various applications. Most existing work mines opinions in Twitter by performing sentiment analysis on the text of tweets. However, a user's opinion towards a topic cannot be obtained by using those text-based approaches, when the user hasn't posted any tweet about it yet. In some cases such as launching new products or proposing new policies, the related online comments are unavailable before their release, while inferring users' opinions towards them beforehand could be potentially helpful for making correct decisions. Therefore, how to predict a user's opinions towards topics without observing the corresponding tweets from him/her, becomes a novel problem presenting both challenges and opportunities. We focus on the problem of predicting user-topic opinions, and propose a framework mph{ScTcMF} for incorporating social and topical context to solve it. The experimental results on a real-world Twitter dataset show that our framework outperforms the state-of-the-art collaborative filtering methods, and demonstrate that both social context and topical context are effective in improving the prediction performance. (Keyword) User-topic opinion prediction / Twitter / social context / topical context (Link to Publication Site) ● Publication site (DOI): 10.1109/T-AFFC.2013.22 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/T-AFFC.2013.22 (DOI: 10.1109/T-AFFC.2013.22)
202.	Fuji Ren, Bo Li and Qimei Chen : Single Parameter Logarithmic Image Processing For Edge detection, IEICE Transactions on Information and Systems, Vol.E96-D, No.11, 2437-2449, 2013. (Summary) Considering the non-linear properties of the human visual system, many non-linear operators and models have been developed, particularly the logarithmic image processing (LIP) model proposed by Jourlin and Pinoli, which has been proved to be physically justified in several laws of the human visual system and has been successfully applied in image processing areas. Recently, several modifications based on this logarithmic mathematical framework have been presented, such as parameterized logarithmic image processing (PLIP), pseudo-logarithmic image processing, homomorphic logarithmic image processing. In this paper, a new single parameter logarithmic model for image processing with an adaptive parameter-based Sobel edge detection algorithm is presented. On the basis of analyzing the distributive law, the subtractive law, and the isomorphic property of the PLIP model, the five parameters in PLIP are replaced by a single parameter to ensure the completeness of the model and physical constancy with the nature of an image, and then an adaptive parameter-based Sobel edge detection algorithm is proposed. By using an image noise estimation method to evaluate the noise level of image, the adaptive parameter in the single parameter LIP model is calculated based on the noise level and grayscale value of a corresponding image area, followed by the single-parameter LIP-based Sobel operation to overcome the noise-sensitive problem of classical LIP-based Sobel edge detection methods, especially in the dark area of an image, while retaining edge sensitivity. Compared with the classical LIP and PLIP model, the given single parameter LIP achieves satisfactory results in noise suppression and edge accuracy. (Keyword) Image edge detection / single parameter logarithmic image processing / image noise measurement (Link to Publication Site) ● Publication site (DOI): 10.1587/transinf.E96.D.2437 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1390282679355611264 ● Search Scopus @ Elsevier (DOI): 10.1587/transinf.E96.D.2437 (DOI: 10.1587/transinf.E96.D.2437, CiNii: 1390282679355611264)
203.	Yimin Tang and Fuji Ren : Universal Triple I Method for Fuzzy Reasoning and Fuzzy Controller, Iranian Journal of Fuzzy Systems, Vol.10, No.5, 1-24, 2013. (Summary) As a generalization of the triple I method, the universal triple Imethod is investigated from the viewpoints of both fuzzy reasoningand fuzzy controller. The universal triple I principle is putforward, which improves the previous triple I principle. Then,unified form of universal triple I method is established based onthe (0,1)-implication or R-implication. Moreover, the reversibilityproperty of universal triple I method is analyzed from expansion,reduction and other type operators, which demonstrate that itsreversibility property seems fine, especially for the case employingthe (0,1)-implication. Lastly, we analyze the response ability offuzzy controllers based on universal triple I method, then thepracticability of triple I method is improved. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84906324536 (Elsevier: Scopus)
204.	Kunxia Wang, Lian Li, Jing Yang and Fuji Ren : Speech Emotion Recognition Using a Novel Feature Set, Journal of Computational Information Systems, Vol.9, No.15, 6097-6104, 2013. (Summary) Speech emotion recognition has attracted attentions from increased number of researchers in Psychology,Computer science,Phonetics and related disciplines.This paper discusses combining multiple features forspeech emotion recognition to yield improved performance. It proposes using combination of multiplefeatures to improve recognition performance. Using ChineseLDC emotional database, the experimentresults show that a novel feature set of MFCC, fundamental frequency, MFCC, MFCC, energy,zero-crossing ratio and amplitude can get the best performance as 95% and 84% for emotional speechrecognition of four emotional state and six emotional state. (Keyword) Speech Emotion Recognition / Support Vector Machine / Feature Set (Link to Publication Site) ● Publication site (DOI): 10.12733/jcisP0241 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84883027296 (DOI: 10.12733/jcisP0241, Elsevier: Scopus)
205.	Ji Li and Fuji Ren : Hybrid Approach for Word Emotion Recognition, IEEJ Transactions on Electrical and Electronic Engineering (TEEE), Vol.8, No.6, 616-626, 2013. (Summary) In recent years, with plenty of online resources constantly emerging, emotion recognition in text has become increasingly important in human-computer interaction. Word emotion plays a very important role in emotion analysis of sentences or documents. This paper proposes a hybrid approach to recognize word emotion in the dimension of eight emotion categories with corresponding intensities based on the Chinese emotion corpus. First, we present a new algorithm of semantic similarity computation for aiding emotion intensity computation, and design a new algorithm of emotion vector computation by making use of both morpheme characteristics and semantic relations. And then, we adopt Support Vector Machines (SVM) model for the secondary classification to the words whose emotions can not be calculated by the semantic analysis algorithm. Our approach achieves the accuracy of 54.00% and 78.75% for exact match and all five types of hit respectively on the basis of the core emotion lexicon CL4. Experimental results show that the integration of morpheme characteristics and semantic relations can improve the classification accuracy efficiently. (Keyword) emotion recognition / emotion vector / natural language processing / morpheme / semantic similarity (Link to Publication Site) ● Publication site (DOI): 10.1002/tee.21905 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1002/tee.21905 (DOI: 10.1002/tee.21905)
206.	Degen HUANG, Shanshan WANG and Fuji Ren : Creating Chinese-English Comparable Corpora, IEICE Transactions on Information and Systems, Vol.E96-D, No.8, 1853-1861, 2013. (Summary) Comparable Corpora are valuable resources for many NLP applications, and extensive research has been done on information mining based on comparable corpora in recent years. While there are not enough large-scale available public comparable corpora at present, this paper presents a bi-directional CLIR-based method for creating comparable corpora from two independent news collections in different languages. The original Chinese document collections and English documents collections are crawled from XinHuaNet respectively and formatted in a consistent manner. For each document from the two collections, the best query keywords are extracted to represent the essential content of the document, and then the keywords are translated into the language of the other collection. The translated queries are run against the collection in the same language to pick up the candidate documents in the other language and candidates are aligned based on their publication dates and the similarity scores. Results show that our approach significantly outperforms previous approaches to the construction of Chinese-English comparable corpora. (Keyword) Comparable Corpora / cross language information retrieval / keyword extraction / document alignment (Link to Publication Site) ● Publication site (DOI): 10.1587/transinf.E96.D.1853 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1390282679354705024 ● Search Scopus @ Elsevier (DOI): 10.1587/transinf.E96.D.1853 (DOI: 10.1587/transinf.E96.D.1853, CiNii: 1390282679354705024)
207.	Fuji Ren, Changqin Quan and Kazuyuki Matsumoto : ENRICHING MENTAL ENGINEERING, International Journal of Innovative Computing, Information and Control, Vol.9, No.8, 3271-3286, 2013. (Summary) The new growing research eld of Affective Computing (AC) provides a newhorizon for quantitative analysis of human emotional states using IT techniques. In thispaper, a new academic system called nriching Mental Engineering (EME)" is proposedfor the problem of mental health from the view of engineering. EME is being establishedas an academic discipline, by being keenly aware of the poverty of the mind from whichpeople living in modern society suffer. In EME, quantitative measurement of richness ofthe mind is regarded as a central technique. This is measured from the information likesubject physiological data, textual information, behavior, and tone of voice. Meanwhile,EME also systemizes external stimuli by an emotional energy function. The emotionenergy function is proposed to calculate a person's emotional stimuli at a certain pointfrom factors like choice of words, voice, facial expressions, physiological information, andbehavior. Furthermore, an application of EME is illustrated through an analysis of thedepressive tendencies in blogs. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84880108523 (Elsevier: Scopus)
208.	Yu Gu, Yusheng Ji, Ji Li, Fuji Ren and Baohua Zhao : EMS: Efficient Mobile Sink Scheduling in Wireless Sensor Networks, Ad Hoc Networks, Vol.11, No.5, 1556-1570, 2013. (Summary) Sink scheduling, in the form of scheduling multiple sinks among the available sink sites to relieve the level of traffic burden, is shown to be a promising scheme in wireless sensor networks (WSNs). However, the problem of maximizing the network lifetime via sink scheduling remains quite a challenge since routing issues are tightly coupled. Previous approaches on this topic either suffer from poor performance due to a lack of joint considerations, or are based on relaxed constraints. Therefore, in this paper, we aim to fill in the research blanks. First, we develop a novel notation Placement Pattern (PP) to bound time-varying routes with the placement of sinks. This bounding technique transforms the problem from time domain into pattern domain, and thus, significantly decreases the problem complexity. Then, we formulate this optimization in a pattern-based way and create an efficient Column Generation (CG) based approach to solve it. Simulations not only demonstrate the efficiency of the proposed algorithm but also substantiate the importance of sink mobility for energy-constrained WSNs. (Keyword) Sink mobility / Wireless sensor networks / Column generation / Lifetime upper bound (Link to Publication Site) ● Publication site (DOI): 10.1016/j.adhoc.2012.11.010 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1016/j.adhoc.2012.11.010 (DOI: 10.1016/j.adhoc.2012.11.010)
209.	Elmarhoumy Mahmoud, Fattah Abdel Mohamed, Motoyuki Suzuki and Fuji Ren : A New Modified Centroid Classifier Approach for Automatic Text Classification, IEEJ Transactions on Electrical and Electronic Engineering (TEEE), Vol.8, No.4, 364-370, 2013. (Summary) To enhance the automatic text classification task, this paper proposes a novel approach for treating the problem of inductive bias incurred by the centroid classifier assumption. This approach is a trainable classifier, which takes into account tfidf as a text feature. The main goal of the proposed approach is to take advantage of the most similar training errors in the classification model for successively updating that model based on a certain threshold. The proposed approach is practical and flexible to implement. The complete performance of the proposed approach is measured at several threshold values on the Reuters-21578 text categorization collection. Experimental results show that the proposed approach can improve the performance of the centroid classifier better than traditional approaches (traditional centroid classifier, support vector machines, decision trees, Bayes nets, and N Bayes) by 1, 1.2, 4.1, 7.5, and 11%, respectively. (Keyword) Text classification / text categorization / centroid classifier / vector space model / modified centroid classifier (Link to Publication Site) ● Publication site (DOI): 10.1002/tee.21867 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1002/tee.21867 (DOI: 10.1002/tee.21867)
210.	Fuji Ren and XIN KANG : Employing Hierarchical Bayesian Networks in Simple and Complex Emotion Topic Analysis, Computer Speech & Language, Vol.27, No.4, 943-968, 2013. (Summary) Traditional emotion models, when tagging single emotions in documents, often ignore the fact that most documents convey complex human emotions. In this paper, we join emotion analysis with topic models to find complex emotions in documents, as well as the intensity of the emotions, and study how the document emotions vary with topics. Hierarchical Bayesian networks are employed to generate the latent topic variables and emotion variables. On average, our model on single emotion classification outperforms the traditional supervised machine learning models such as SVM and Naive Bayes. The other model on the complex emotion classification also achieves promising results. We thoroughly analyze the impact of vocabulary quality and topic quantity to emotion and intensity prediction in our experiments. The distribution of topics such as Friend and Job are found to be sensitive to the documents' emotions, which we call emotion topic variation in this paper. This reveals the deeper relationship between topics and emotions. (Keyword) Emotion classification / Emotion topic model / Complex emotion / Hierarchical Bayesian network (Link to Publication Site) ● Publication site (DOI): 10.1016/j.csl.2012.07.012 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84875925315 (DOI: 10.1016/j.csl.2012.07.012, Elsevier: Scopus)
211.	Elmarhoumy Mahmoud and Fuji Ren : A New Hybrid Model for Automatic Text Classification, The Online Journal on Computer Science and Information Technology, OJCSIT, Vol.3, No.2, 132-137, 2013. (Summary) This paper introduces three novel pointes the first one is creating the proposed tfsc,dfsc algorithm to sort the terms in N-gram model which effected goodly on the classification performance. The second one is proposing a new distance similarity method for N-gram model where the new method solves the problem of the difference in representation lengths among classes and documents. The third one is establishing a hybrid Center Profile Vector (CPV) classification model based on the modified N-gram and centroid classifier models. The hybrid (CPV) classification model gain a higher classification accuarcy beteer than N-gram and centroid models as the paper will show in the evaluation result. (Keyword) Hybrid CPV model / Text Classification / Centroid Classifier / N-gram / VSM
212.	Fuji Ren and Sohrab Golam Mohammad : Class-indexing-based term weighting for automatic text classification, Information Sciences, Vol.236, No.1, 109-125, 2013. (Summary) Most of the previous studies related on different term weighting emphasize on the document- indexing-based and four fundamental information elements-based approaches to address automatic text classification (ATC). In this study, we introduce class-indexingbased term-weighting approaches and judge their effects in high-dimensional and comparatively low-dimensional vector space over the TF.IDF and five other different term weighting approaches that are considered as the baseline approaches. First, we implement a class-indexing-based TF.IDF.ICF observational term weighting approach in which the inverse class frequency (ICF) is incorporated. In the experiment, we investigate the effects of TF.IDF.ICF over the Reuters-21578, 20 Newsgroups, and RCV1-v2 datasets as benchmark collections, which provide positive discrimination on rare terms in the vector space and biased against frequent terms in the text classification (TC) task. Therefore, we revised the ICF function and implemented a new inverse class space density frequency (ICSdF), and generated the TF.IDF.ICSdF method that provides a positive discrimination on infrequent and frequent terms. We present detailed evaluation of each category for the three datasets with term weighting approaches. The experimental results show that the proposed class-indexing-based TF.IDF.ICSdF term weighting approach is promising over the compared well-known baseline term weighting approaches. (Keyword) Text classification / Indexing / Term weighting / machine learning / Feature selection / Classifier (Link to Publication Site) ● Publication site (DOI): 10.1016/j.ins.2013.02.029 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1016/j.ins.2013.02.029 (DOI: 10.1016/j.ins.2013.02.029)
213.	Changqin Quan and Fuji Ren : Finding Emotional Focus for Emotion Recognition at Sentence Level, Chinese Journal of Electronics, Vol.22, No.1, 99-103, 2013. (Summary) Emotion recognition at sentence level is one of the fundamental problems of textual emotion understanding. Based on the observation that sentence emotional focus can be expressed by some clauses in this sentence, this paper proposes to find the emotional focus for sentence emotion recognition. For the sake of breaking through the problems brought about by depending on emotion lexicons, we first recognize word emotions in a sentence based on Maximum entropy model. And then homogeneous Markov model is built for clause emotion recognition; After that, a strategy based on emotion selection is proposed for a sentence with multiple clauses, and genetic algorithm is used for clause selection by textual feature weighting. The experimental results show that, comparing with the baseline, there are 9.1% and 3.6% improvement respectively for two different evaluations. It is demonstrated that finding emotional focus by clause selection is able to improve the performance of sentence emotion recognition significantly. (Keyword) Sentence emotion recognition / Feature extraction / Maximum entropy / Homogeneous Markov / Genetic algorithm (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84875532884 (Elsevier: Scopus)
214.	Shin-ichi Chiba, Narimasa Watanabe, Tetsuya Tanioka, Yukie Iwasa, Kyoko Osaka, Yuko Yasuhara, Chiemi Kawanishi, Fuji Ren, Hiroshi Ogasawara and Kazushi Mifune : Use of a Dialogue System to Retrieve the Memories of Elderly Individuals with Dementia and Determine the Physiologically Effective Evaluation Indicators, International Journal of Advanced Intelligence (IJAI), Vol.4, No.1, 43-54, 2012.
215.	Yuko Yasuhara, Chiho Tamayama, Kana Kikukawa, Kyoko Osaka, Tetsuya Tanioka, Narimasa Watanabe, Shin-ichi Chiba, Masami Miyoshi, Rozzano De Castro Locsin, Fuji Ren, Shoko Fuji, Hiroshi Ogasawara and Kazushi Mifune : Required Function of the Caring Robot with Dialogue Ability for Patients with Dementia, AIA International Advanced Information Institute, Vol.4, No.1, 31-42, 2012.
216.	Seiji Tsuchiya, Motoyuki Suzuki, Fuji Ren and Hirokazu Watabe : A Novel Estimation Method of Onomatopoeic Word's Feeling based on Mora Sequence Patterns and Felling Vectors, Journal of Natural Language Processing, Vol.19, No.5, 367-379, 2012. (Summary) Onomatopoeic words are frequently used for expression of rich presence. These words can be understood easily for native speakers. Therefore most of onomatopoetic words are not written in a national language dictionary, or only a part of meaning is described. On the other hand, it is hard to understand a meaning of onomatopoetic words for non-native speakers. They can neither feel a meaning of an onomatopoetic word nor look it up in a dictionary. In this paper, an estimation method of feeling of an onomatopoeic word has been proposed. The feeling of the onomatopoeic word is inferred by using several features, such as morae sequence pattern of a onomatopoeic word, feeling of each mora, and so on. From the experimental results, the estimation performance of the proposed method was 0.345 (F-value). It was approximately 80% of the estimation performance given by human (F-value was 0.427). It can be said that the proposed method is useful for supporting learners of onomatopoeic words. (Keyword) オノマトペ / 印象推定 / モーラ系列 / 音象徴ベクトル / Onomatopoeic word / Estimation of feeling / Mora Sequence Patterns / Feeling Vectors (Link to Publication Site) ● Publication site (DOI): 10.5715/jnlp.19.367 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1390001204474518272 ● Search Scopus @ Elsevier (DOI): 10.5715/jnlp.19.367 (DOI: 10.5715/jnlp.19.367, CiNii: 1390001204474518272)
217.	Ji Li and Fuji Ren : Emotion Recognition of Weblog Sentences Based on an Ensemble Algorithm of Multi-label Classification and Word Emotions, IEEJ Transactions on Electronics, Information and Systems, Vol.132, No.8, 1362-1375, 2012. (Summary) Weblogs have greatly changed the communication ways of mankind. Affective analysis of blog posts is found valuable for many applications such as text-to-speech synthesis or computer-assisted recommendation. Traditional emotion recognition in text based on single-label classification can not satisfy higher requirements of affective computing. In this paper, the automatic identification of sentence emotion in weblogs is modeled as a multi-label text categorization task. Experiments are carried out on 12273 blog sentences from the Chinese emotion corpus Ren_CECps with 8-dimension emotion annotation. An ensemble algorithm RAKEL is used to recognize dominant emotions from the writers perspective. Our emotion feature using detailed intensity representation for word emotions outperforms the other main features such as the word frequency feature and the traditional lexicon-based feature. In order to deal with relatively complex sentences, we integrate grammatical characteristics of punctuations, disjunctive connectives, modification relations and negation into features. It achieves 13.51% and 12.49% increases for Micro-averaged F1 and Macro-averaged F1 respectively compared to the traditional lexicon-based feature. Result shows that multiple-dimension emotion representation with grammatical features can efficiently classify sentence emotion in a multi-label problem. (Keyword) Emotion Recognition / Weblog / Natural Language Processing / Multi-label Classification / Machine Learning (Link to Publication Site) ● Publication site (DOI): 10.1541/ieejeiss.132.1362 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1390001204607806336 ● Search Scopus @ Elsevier (DOI): 10.1541/ieejeiss.132.1362 (DOI: 10.1541/ieejeiss.132.1362, CiNii: 1390001204607806336)
218.	Fuji Ren and Changqin Quan : Linguistic-Based Emotion Analysis and Recognition for Measuring Consumer Satisfaction - An Application of Affective computing, Information Technology and Management, Vol.13, No.4, 321-332, 2012. (Summary) A growing body of research suggests that affective computing has many valuable applications in enterprise systems research and e-businesses. This paper explores affective computing techniques for a vital subarea in enterprise systems consumer satisfaction measurement. We propose a linguistic-based emotion analysis and recognition method for measuring consumer satisfaction. Using an annotated emotion corpus (Ren-CECps), we first present a general evaluation of customer satisfaction by comparing the linguistic characteristics of emotional expressions of positive and negative attitudes. The associations in four negative emotions are further investigated. After that, we build a fine-grained emotion recognition system based on machine learning algorithms for measuring customer satisfaction; it can detect and recognize multiple emotions using customers' words or comments. The results indicate that blended emotion recognition is able to gain rich feedback data from customers, which can provide more appropriate follow-up for customer relationship management. (Keyword) Affective computing / Enterprise systems / Linguistic feature / Customer satisfaction (Link to Publication Site) ● Publication site (DOI): 10.1007/s10799-012-0138-5 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84868656112 (DOI: 10.1007/s10799-012-0138-5, Elsevier: Scopus)
219.	Yiming Tang, Fuji Ren and Yanxiang Chen : Differently implicational -universal triple I restriction method of (1, 2, 2) type, Journal of Systems Engineering and Electronics, Vol.23, No.4, 560-573, 2012. (Summary) From the viewpoints of both fuzzy system and fuzzy reasoning, a new fuzzy reasoning method which contains the -triple I restriction method as its particular case is proposed. The previous -triple I restriction principles are improved, and then the optimal restriction solutions of this new method are achieved, especially for seven familiar implications. As its special case, the corresponding results of -triple I restriction method are obtained and improved. Lastly, it is found by examples that this new method is more reasonable than the -triple I restriction method. (Link to Publication Site) ● Publication site (DOI): 10.1109/JSEE.2012.00070 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/JSEE.2012.00070 (DOI: 10.1109/JSEE.2012.00070)
220.	Wei Wang, Fuji Ren and Motoyuki Suzuki : A Novel Fast Fractal Image Coding Algorithm Based on Texture Feature, IEEJ Transactions on Electrical and Electronic Engineering (TEEE), Vol.7, No.5, 521-528, 2012. (Summary) A novel, fast fractal image coding algorithm based on the texture feature is proposed in this paper. Fractal image coding isa very promising technique for image compression. However, it has not been widely used because of the long encoding timeand high computational complexity. The most fractal image encoding time is spent in determining the approximate D-blockfrom a large D-blocks library by using the global searching method. Clustering the D-blocks library is an effective method toreduce the encoding time. First, all the D-blocks are clustered into several parts based on the new texture feature derived fromvariation function; second, for each R-block, the approximate D-blocks are searched for in the same part. In the search process,we import control parameter ; this step avoids losing the most approximate D-block for each R-block. Finally, the R-blockswhose least errors are larger than the threshold given in advance are coded by the quad tree method. We have performed asimulation with MATLABR2010a to verify the effectiveness of the proposed algorithm. The experimental results show that theproposed algorithm can be over 6 times faster than the moment-feature-based fractal image algorithm; in addition, the proposedalgorithm also improves the quality of the decoded image and increases the PSNRs average value by 2 dB. The comparisonsdemonstrate that this method is better than the fractal image coding algorithm based on statistical features (Link to Publication Site) ● Publication site (DOI): 10.1002/tee.21768 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1002/tee.21768 (DOI: 10.1002/tee.21768)
221.	Guangwei Xu, Ming Zhu, Xin Luo, Min Wu and Fuji Ren : An unequal clustering algorithm based on energy balance for wireless sensor networks, IEEJ Transactions on Electrical and Electronic Engineering (TEEE), Vol.7, No.4, 402-407, 2012. (Summary) Sensor nodes in sensor networks often gather data and deliver them to the sink. However, the energy and radio range constraints force them to cooperate in transmitting the data to the destination with multihop communication. To achieve this, nodes have to be clustered and some of them are elected as the cluster head nodes to transmit the aggregated data. Unfortunately, the clustering brings extra traffic load to the cluster head nodes, particularly those closer to the sink. These nodes die faster than before as their energy is drained at a high rate. Therefore, some clustering and cluster head election algorithms were suggested to use the unequal clustering size to extend the lifetime of cluster head nodes. However, it is difficult to obtain the accurate cluster size in the process of unequal clustering. Moreover, some cluster head nodes with the overfull cluster members may die early. We propose an enhanced unequal clustering size algorithm to optimize the unequal cluster size in the different layers and balance the dissipation energy of all cluster head nodes. Simulation results show that our algorithm dissipates approximately the same energy of cluster head nodes in the different layers per round and obviously increases the number of rounds of data gathering and transmission. (Link to Publication Site) ● Publication site (DOI): 10.1002/tee.21747 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1002/tee.21747 (DOI: 10.1002/tee.21747)
222.	Peilin Jiang, Fei Wang and Fuji Ren : Semi-Automatic Complex Emotion Categorization and Ontology Construction from Chinese Knowledge, China Communications, Vol.9, No.3, 28-37, 2012. (Summary) In order to recognize one's intention from the communication, both the meaning and the emotion are necessary to be interpreted correctly. But until now the study of fine-grained theory of emotion is still full of challenges. This paper analy-zes emotion category according to the statistics of Affective Word (AW) hierarchy and describes an e-motion ontology from Chinese knowledge resource semi-automatically created for human machine in-teraction. The emotion hierarchy is called complex emotion. Firstly, over 7 000 AWs have been anno-tated and their detailed explanations had been col-lected for an affective lexicon and then the con-sistent relationships are automatically parsed and a serial of emotion hierarchical structures are built up. More than 50 affective categories are extracted by a lexical clustering algorithm and about 5 000 nouns and adjectives and 2 000 verbs are categorized into the predicate hierarchy. The results have been evalu-ated to be valid by two metrics. (Keyword) natural language processing / affective computing / emotion ontology / emotion-top-ic variation / AW annotation (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84861779338 (Elsevier: Scopus)
223.	Kazuyuki Matsumoto, Kenji Kita and Fuji Ren : Emotional Vector Distance Based Sentiment Analysis of Wakamono Kotoba, China Communications, Vol.9, No.3, 87-98, 2012. (Summary) In this paper, we propose a method for estimating emotion in Wakamono Kotoba that were not registered in the system, by using Wakamono Kotoba example sentences as features. The proposed method applies Earth Mover's Distance(EMD) to vector of words. As a result ofthe evaluation experiment using 14,440 sentences, higher estimation accuracy is obtained by considering emotional distance between words - an approach that had not been used in the conventional research - than by using only word importance value. (Keyword) Wakamono Kotoba / sentiment analysis / emotion estimation / Earth Mover's Distance (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84861787581 (Elsevier: Scopus)
224.	XIN KANG and Fuji Ren : Predicting Complex Word Emotions and Topics through a Hierarchical Bayesian Network, China Communications, Vol.9, No.3, 99-109, 2012. (Summary) In this paper, we provide a Word Emotion Topic (WET) model to predict the complex word e-motion information from text, and discover the dis-tribution of emotions among different topics. A complex emotion is defined as the combination of one or more singular emotions from following 8 basic emotion categories: joy, love, expectation, surprise, anxiety, sorrow, anger and hate. We use a hierarchical Bayesian network to model the emo-tions and topics in the text. Both the complex emo-tions and topics are drawn from raw texts, without considering any complicated language features. Our experiment shows promising results of word emo-tion prediction, which outperforms the traditional parsing methods such as the Hidden Markov Model and the Conditional Random Fields(CRFs) on raw text. We also explore the topic distribution by ex-amining the emotion topic variation in an emotion topic diagram. (Keyword) word emotion classification / complex emotion / emotion intensity prediction / emotion-top-ic variation / hierarchical Bayesian network (Tokushima University Institutional Repository) ● Metadata: 118261 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84861773080 (Tokushima University Institutional Repository: 118261, Elsevier: Scopus)
225.	Fang Tian, Caixia Yuan and Fuji Ren : Hyponym Extraction from the Web by Bootstrapping, IEEJ Transactions on Electrical and Electronic Engineering (TEEE), Vol.7, No.1, 62-68, 2012. (Summary) This paper proposes an effective method to automatically extract hyponym from the Web for Chinese. The method extractshyponyms for a given hypernym through weak supervision in two stages: the first stage is submitting a hypernym and a seedhyponym as a query to Web search engine, and automatically extracting hyponyms matching with a Chinese doubly anchoredhyponymy pattern from the Web by bootstrapping. In order to reduce noise data in bootstrapping extraction, we propose a set offiltering rules to ensure matching of the proper hypernym in the extracted sentence. The second stage is ranking all the extractedcandidate hyponyms by an integrated ranking algorithm which takes into account measures both of linkage frequency betweencoordinate hyponyms and of semantic similarity between the hypernym and candidate hyponym based on co-occurrence statistics. (Keyword) hyponym / hypernym / hyponym acquisition / bootstrapping / Web search engine (Link to Publication Site) ● Publication site (DOI): 10.1002/tee.21696 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1002/tee.21696 (DOI: 10.1002/tee.21696)
226.	Yunong Wu, Kenji Kita, Fuji Ren, Kazuyuki Matsumoto and XIN KANG : Exploring the Importance of Modification Relation for Emotional Keywords Annotation and Emotion Types Recognition, International Journal of Intelligent Engineering and Systems, Vol.4, No.4, 19-26, 2011. (Summary) In this study, we make a scheme to explore the importance of modification relation for the emotional keywords annotation and emotion types recognition. We extract three modification features which are degree words,negative words and conjunctions from the Chinese emotion corpus named Ren-CECps. Beside word and part-of speech,three modification relations are adopted as feature in this study. We have carried out eight experiments with different feature sets for emotional keywords annotation and emotion types recognition in sentence level. Eight basic emotion types have been selected and Conditional Random Fields have been employed as the algorithm. In the part of evaluation, we demonstrate the importance of the modification features and our experiment results show the effectiveness of the modification features for improving the performance of emotional keywords annotation and emotion types recognition. (Keyword) Emotional Keywords Annotation / Emotion types recognition / Modification relation / CRFs (Link to Publication Site) ● Publication site (DOI): 10.22266/ijies2011.1231.03 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84859614924 (DOI: 10.22266/ijies2011.1231.03, Elsevier: Scopus)
227.	Yiming Tang, Fuji Ren and Yanxiang Chen : Reversibility of FMT-Universal Triple I Method Based on IL Operator, American Journal of Engineering and Technology Research, Vol.11, No.12, 2763-2766, 2011. (Summary) For the FMT-universal triple I method based on L I operator, its reversibility is investigated. Aiming at thecase that the second operator employs L I , the reversibility of FMT-universal triple I method is analyzed, where the firstoperator respectively takes seven different implication operators. It is found that the FMT-universal triple I methodseems excellent from the viewpoint of reversibility, and the second operator prefers to take L I in the universal triple Imethod.
228.	Huiwei Zhou, Xiaoyan Li, Degen Huang, Yuansheng Yang and Fuji Ren : Voting-Based Ensemble Classifiers to Detect Hedges and Their Scopes in Biomedical Texts, IEICE Transactions on Information and Systems, Vol.E94-D, No.10, 1989-1997, 2011. (Summary) Previous studies of pattern recognition have shown that classifiers ensemble approaches can lead to better recognition results. In this paper, we apply the voting technique for the CoNLL-2010 shared task on detecting hedge cues and their scope in biomedical texts. Six machine learning-based systems are combined through three different voting schemes. We demonstrate the effectiveness of classifiers ensemble approaches and compare the performance of three different voting schemes for hedge cue and their scope detection. Experiments on the CoNLL-2010 evaluation data show that our best system achieves an F-score of 87.49% on hedge detection task and 60.87% on scope finding task respectively, which are significantly better than those of the previous systems. (Keyword) hedges / voting / classification / machine learning (Link to Publication Site) ● Publication site (DOI): 10.1587/transinf.E94.D.1989 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1390001204378835200 ● Search Scopus @ Elsevier (DOI): 10.1587/transinf.E94.D.1989 (DOI: 10.1587/transinf.E94.D.1989, CiNii: 1390001204378835200)
229.	Kazuyuki Matsumoto and Fuji Ren : Estimation of word emotions based on part of speech and positional information, Computers in Human Behavior, Vol.27, No.5, 1553-1564, 2011. (Summary) Recently, studies on emotion recognition technology have been conducted in the fields of natural language processing, speech signal processing, image data processing, and brain wave analysis, with the goal of letting the computer understand ambiguous information such as emotion or sensibility. This paper statistically studies the features of Japanese and English emotional expressions based on an emotion annotated parallel corpus and proposes a method to estimate emotion of the emotional expressions in the sentence. The proposed method identifies the words or phrases with emotion, which we call emotional expressions, and estimates the emotion category of the emotional expressions by focusing on the three kinds of features: part of speech of emotional expression, position of emotional expression, and part of speech of the previous/next morpheme of the target emotional expression. (Keyword) Emotion recognition / Emoton corpus / Sensibility (Link to Publication Site) ● Publication site (DOI): 10.1016/j.chb.2010.10.028 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1016/j.chb.2010.10.028 (DOI: 10.1016/j.chb.2010.10.028)
230.	Kazuyuki Matsumoto, Hidemichi Sayama, Yusuke Konishi and Fuji Ren : Analysis of Wakamono Kotoba Emotion Corpus and Its Application in Emotion Estimation, International Journal of Advanced Intelligence (IJAI), Vol.3, No.1, 1-24, 2011. (Summary) Recently, there is a lot of research that aims to estimate emotion from text. The meaningsof linguistic expressions used in daily life vary depending on the context in which theyare used. That is to say, the information they contain presents ambiguities. Especiallythe so-called Wakamono Kotoba, Japanese language used by young people containssemantic ambiguities. Such words are usually not included in the existing dictionaries,making the meanings of these words difficult to be recognized. In this research projectwe proposed a method to estimate emotion from sentences that include Wakamono Kotobaby using statistical learning methods such as Na¨ıve Bayes method and Accumulationmethod. The existing research usually focused on learning methods using word or wordN-gram as features. However, such word-based features are insufficient to process WakamonoKotoba because Wakamono Kotoba often cannot be recognized as one semanticword by morphological analysis. In this paper we describe how we constructed the linguisticresource of Wakamono Kotoba emotion corpus to be used for emotion recognitionand introduce the features we obtained from statistical analysis. Our Wakamono Kotobaemotion corpus includes Japanese words used by young people to express emotion. Thesewere mainly gathered from Weblogs that were written by young people from their teensto their twenties. (Keyword) Emotion Recognition / Wakamono Kotoba / Emotion Corpus
231.	Xiao Sun, Degen Huang, Haiyu Song and Fuji Ren : Chinese New Word Identification: A Latent Discriminative Model with Global Features, Journal of Computer Science and Technology, Vol.26, No.1, 14-24, 2011. (Summary) Chinese new words are particularly problematic in Chinese natural language processing. With the fast development of Internet and information explosion, it is impossible to get a complete system lexicon for applications in Chinese natural language processing, as new words out of dictionaries are always being created. The procedure of new words identification and POS tagging are usually separated and the features of lexical information cannot be fully used. A latent discriminative model, which combines the strengths of Latent Dynamic Conditional Random Field (LDCRF) and semi-CRF, is proposed to detect new words together with their POS synchronously regardless of the types of new words from Chinese text without being pre-segmented. Unlike semi-CRF, in proposed latent discriminative model, LDCRF is applied to generate candidate entities, which accelerates the training speed and decreases the computational cost. The complexity of proposed hidden semi-CRF could be further adjusted by tuning the number of hidden variables and the number of candidate entities from the Nbest outputs of LDCRF model. A new-word-generating framework is proposed for model training and testing, under which the definitions and distributions of new words conform to the ones in real text. The global feature called Global Fragment Features for new word identification is adopted. We tested our model on the corpus from SIGHAN-6. Experimental results show that the proposed method is capable of detecting even low frequency new words together with their POS tags with satisfactory results. The proposed model performs competitively with the state-of-the-art models. (Keyword) new word identification / new words POS tagging / conditional random fields / hidden semi-CRF / global fragment features (Link to Publication Site) ● Publication site (DOI): 10.1007/s11390-011-9411-z (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1007/s11390-011-9411-z (DOI: 10.1007/s11390-011-9411-z)
232.	Changqin Quan and Fuji Ren : Recognition of Word Emotion State in Sentences, IEEJ Transactions on Electrical and Electronic Engineering (TEEE), Vol.6, No.S1, 34-41, 2011. (Summary) Emotional word spotting has been an important step for the problems of textual emotion recognition and automatic emotionlexicon construction. To express and recognize emotion of words, especially for the words bear undirect emotions, emotionambiguity, or multiple emotions, the notion of word emotion state is proposed, which describes the state of combined basicemotions in a word. On the basis of Ren-CECps (an annotated emotion corpus) and MaxEnt (maximum entropy) modeling,we explore the effectiveness of several features and their combinations for word emotion recognition in certain contexts. Acomparative study on the performances of word emotion and word emotion state recognition is given. The experimental resultsshowed that a model using word emotion state can greatly outperform using word emotion. (Keyword) emotion recognition / word emotion state / Ren-CECps / MaxEnt (Link to Publication Site) ● Publication site (DOI): 10.1002/tee.20618 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1570572700873383040 ● Search Scopus @ Elsevier (DOI): 10.1002/tee.20618 (DOI: 10.1002/tee.20618, CiNii: 1570572700873383040)
233.	Kenichi Mishina, Seiji Tsuchiya, Motoyuki Suzuki and Fuji Ren : An Improvement of Example-based Emotion Estimation Using Similarity between Sentence and each Corpus, Journal of Natural Language Processing, Vol.17, No.4, 91-110, 2010. (Summary) 発話文を感情ごとに分類したコーパスを構築し，入力文と最も類似度が高い発話文を含むコーパスの感情を推定結果として出力する用例ベースの感情推定手法が提案されている．従来手法ではコーパスを構築する際，発話テキストの収集者が個人個人で発話文の分類先を決定しているため，分類先を決定する基準が個々によってぶれてしまう．これにより，例えば``希望''のコーパスの中に喜びの発話文が混じるといったことが起こり，推定成功率を下げてしまう．本稿ではこの問題を解決するため，コーパスごとにおける入力文の形態素列の出現回数を用いて，入力文とコーパスの類似度を定義する．そしてこの類似度を従来手法に導入した新たな類似度計算式を提案する．これにより，誤って分類されてしまった発話文の影響を緩和することができる．評価実験では従来手法と比べて成功率が 21.5 ポイント向上し，提案手法の有効性が確認できた． (Keyword) 感性情報処理 / 類似度計算 / 用例ベース / N-gram / Affective computing / Similar calculation / Example-based (Link to Publication Site) ● Publication site (DOI): 10.5715/jnlp.17.4_91 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1520572359999171968 ● Search Scopus @ Elsevier (DOI): 10.5715/jnlp.17.4_91 (DOI: 10.5715/jnlp.17.4_91, CiNii: 1520572359999171968)
234.	Fuji Ren : From Cloud Computing to Language Engineering, Affective Computing and Advanced Intelligence, International Journal of Advanced Intelligence (IJAI), Vol.2, No.1, 1-14, 2010. (Summary) This paper discusses the definition, intension, and extension of language engineering, affective computing, and advanced intelligence, as well as the relationship among the three fields. By reporting the latest progress and future prospects, we attempt to unify language engineering and affective computing with the concept of advanced intelligence.``Cloud computing'' has recently become a very popular topic. Instead of discussing the concept and intension of cloud computing, this paper focuses on how progress in language engineering, including natural language processing and natural language understanding, will enormously aid in the achievement of cloud computing. It particularly deals with how to construct clouds, how to sweep clouds, and how to predict and exploit clouds.Another concept discussed in this paper is ``affective computing''. To a large extent, this is a breakthrough in advanced intelligence. Here, it refers to a high fusion of natural and artificial intelligence, and depends on the emotional capacity entrusted to the computer, including the capability of affective recognition and affective generation. (Keyword) Language engineering / Affective computing / Advanced intelligence / Cloud computing
235.	Changqin Quan and Fuji Ren : Sentence Emotion Analysis and Recognition Based on Emotion Words Using Ren-CECps, International Journal of Advanced Intelligence (IJAI), Vol.2, No.1, 105-117, 2010. (Summary) Emotion recognition on text has wide applications. In this study, we make an analysis onsentence emotion based on emotion words using Ren-CECps (a Chinese emotion corpus).Some classification methods (including C4.5 decision tree, SVM, NaiveBayes, ZEROR,and DecisionTable) have been compared. Then a supervised machine learning method(Polynomial kernel method) is proposed to recognize the eight basic emotions (Expect,Joy, Love, Surprise, Anxiety, Sorrow, Angry and Hate). Using Ren-CECps, we get theemotion lexicons for the eight basic emotions. Polynomial kernel (PK) method is usedto compute the similarities between sentences and the eight emotion lexicons. Then theexperiential knowledge derived from Ren-CECps is used to recognize whether the eightemotion categories are present in a sentence. The experiments showed promising results. (Keyword) Emotion recognition / Chinese emotion corpus / Classification methods / Polynomial kernel
236.	Xiao Sun, Degen Huang and Fuji Ren : Detecting New Words from Chinese Text Using Latent Semi-CRF Models, IEICE Transactions on Information and Systems, Vol.E93-D, No.6, 1386-1393, 2010. (Summary) Chinese new words and their part-of-speech (POS) are particularly problematic in Chinese natural language processing. With the fast development of internet and information technology, it is impossible to get a complete system dictionary for Chinese natural language processing, as new words out of the basic system dictionary are always being created. A latent semi-CRF model, which combines the strengths of LDCRF (Latent-Dynamic Conditional Random Field) and semi-CRF, is proposed to detect the new words together with their POS synchronously regardless of the types of the new words from the Chinese text without being pre-segmented. Unlike the original semi-CRF, the LDCRF is applied to generate the candidate entities for training and testing the latent semi-CRF, which accelerates the training speed and decreases the computation cost. The complexity of the latent semi-CRF could be further adjusted by tuning the number of hidden variables in LDCRF and the number of the candidate entities from the Nbest outputs of the LDCRF. A new-words-generating framework is proposed for model training and testing, under which the definitions and distributions of the new words conform to the ones existing in real text. Specific features called ``Global Fragment Information'' for new word detection and POS tagging are adopted in the model training and testing. The experimental results show that the proposed method is capable of detecting even low frequency new words together with their POS tags. The proposed model is found to be performing competitively with the state-of-the-art models presented. (Keyword) natural language processing / new word detection / new words POS tagging / conditional random fields / latent-dynamic CRF / semi-CRF / latent semi-CRF (Link to Publication Site) ● Publication site (DOI): 10.1587/transinf.E93.D.1386 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1390282679356135680 ● Search Scopus @ Elsevier (DOI): 10.1587/transinf.E93.D.1386 (DOI: 10.1587/transinf.E93.D.1386, CiNii: 1390282679356135680)
237.	Changqin Quan, Fuji Ren and Tingting He : Sentimental Classification based on Kernel Methods and Domain Semantic Orientation Dictionaries, International Journal of Innovative Computing, Information and Control, Vol.6, No.6, 2681-2690, 2010. (Summary) Kernel-based algorithms exploit the document information encoded in the inner-product between all pairs of document data items, avoiding explicitly the computation of the feature vector for a given input, therefore it gets considerable attention in classification tasks. In this paper, we focus our attention on the problem of sentimental classification based on three kernel methods: latent semantic kernel (LSK), polynomial kernel (PK), and Gaussian kernel (GK). It is well known that LSK has good performance in text classification, but it has relative low efficiency because of the process of the SVD decomposition, especially runs on large corpora. Our experiments demonstrate that PK has higher precision and efficiency compared with LSK and GK for the problem of sentimental classification. In particular, we compared the performances on different semantic orientation dictionaries, and found that the domain semantic orientation dictionaries could enhance the performance greatly. Also, our method could categorize the reviews with different degrees, such as 5-star, 4-star and 1-star by sorting the similarities between the reviews and the semantic orientation dictionaries. In our method, tagged corpus and certain rules are not necessary, so it is practical and has high efficiency. (Keyword) Sentimental classification / Kernel methods / Semantic orientation dictionaries (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-80052475171 (Elsevier: Scopus)
238.	Ye Liu, Zhi Teng and Fuji Ren : A Practical Sightseeing Question Answering System Based on Integrated Knowledge-Base, IEEJ Transactions on Electronics, Information and Systems, Vol.130, No.4, 580-588, 2010. (Summary) In this paper, a restricted domain question answering (QA) system is described. This research presents a practical sightseeing question answering system based on integrated knowledge-base. First, we use hand-crafted corpus and online resources as knowledge-base, then perform question understanding based on sightseeing place word detection and question classification. We exploit different answer extraction strategies while based on various knowledge-base (hand-crafted corpus or online resources) for answer retrieval and generation. Experimental results show the proposed method is effective for improving our former models. (Keyword) sightseeing question answering (QA) system / knowledge-base / hand-crafted corpus / online resources / answer generation (Link to Publication Site) ● Publication site (DOI): 10.1541/ieejeiss.130.580 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1390282679585898752 ● Summary page in Scopus @ Elsevier: 2-s2.0-77953553293 (DOI: 10.1541/ieejeiss.130.580, CiNii: 1390282679585898752, Elsevier: Scopus)
239.	Ai Hakamata, Fuji Ren and Seiji Tsuchiya : Human Emotion Model Based on Discourse Sentence for Expression Generation of Conversation Agent, International Journal of Innovative Computing, Information and Control, Vol.6, No.3(B), 1537-1548, 2010. (Summary) There was a conversation agent on the generation method of facial expression. It is necessary for the conversation system like the human for communication. In the previous method, at first a word which could influence the feeling was defined. Facial expression was changed according to the word which influences the feeling in discourse. Whereas, facial expression could not be changed if there was not a word that was defined in the discourse. Hence, we proposed a human emotion model for the expression generation of the conversation agent. The method based on the human emotion model can solve problem of the previous method and may make a more humanity conversation agent. In this study, we put a human emotion tag to discourse of talks scenarios and model to conversation agent of human emotion. There were two kinds of methods that put the human emotion tag to discourse. We make the human emotion model by scenarios that adopts the human emotion tag. Used the human emotion model to create facial expression of conversation agent. The assessment experiment was performed by using the systems of previous method and two human emotion models, and compared the results between the three methods (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-77950130737 (Elsevier: Scopus)
240.	Liping Mi, Xin Luo and Fuji Ren : An ERP Research on Chinese Japanese Learners' Processing of Japanese Kanji and Sentences, International Journal of Innovative Computing, Information and Control, Vol.6, No.3(B), 1491-1500, 2010. (Summary) This paper investigates the recognition process of Japanese Kanji and sentences for Chinese Japanese learners (CJL) and native Japanese speakers (NJS), by analyzing the event-related potential (ERP) differences between the two groups while they visually recognized Japanese Kanji and sentences The results showed that no significant differences were found between the two groups while they recognized Japanese Kanji, but significant differences were found in Japanese sentences condition, which demonstrated that the neural mechanisms of recognition process of Japanese sentences including Kana between the two groups were not identical The N400 latency of NJS appeared earlier, reflecting that NJS recognized Japanese sentences quicker than CJL did In contrast, the obvious longer N400 duration of CJL illuminated it was more difficult for CJL to recognize Japanese sentences When recognizing ambiguous sentences, CJL P600 only appeared over the right prefrontal cortex and lasted longer than that of NJS, reflecting that syntactic integration and revision of ambiguous sentences for CJL was related with the right hemisphere, and the processing load was more difficult than that of NJS. The results showed that, for CJL, the difficulty of Japanese language learning was the recognition and understanding of Japanese sentences with Kana, not Japanese Kanji (Keyword) Event-related potential / N400; P600 / Semantic processing / Syntactic processing (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-77950159507 (Elsevier: Scopus)
241.	Caixia Yuan, Xiaojie Wang and Fuji Ren : Exploiting Lexical Information for Function Tag Labeling, International Journal of Innovative Computing, Information and Control, Vol.6, No.3(B), 1471-1480, 2010. (Summary) This paper proposes a novel approach to annotate function tags for unparsedtext. What distinguishes our work from previous attempts is that we assign function tagsdirectly basing on lexical information other than on parsed trees, thus our method isgeneral and easily portable to languages in shortage of parsing resources. In order todemonstrate the effectiveness and versatility of our method, we investigate function tagassignment for unparsed Chinese text by applying two statistical models, one is log-linearmaximum entropy model, another is maximum margin based support vector machinemodel. We show that function tag types could be determined via powerful lexical featuresand effective learning algorithms. Currently, our method achieves the best F-score of86.4 when tested on the Penn Chinese Treebank data, the highest score ever reported forChinese text. (Keyword) Function tags / Unparsed text / Penn treebank / Chinese language processing (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-77950152716 (Elsevier: Scopus)
242.	Jia Ma, Motoyuki Suzuki and Fuji Ren : Spokesperson Detection Method for Autonomous Robot in Complex Communication Environment, Based on Image Processing, International Journal of Innovative Computing, Information and Control, Vol.6, No.3(B), 1515-1524, 2010. (Summary) Fro providing a man-machine communication system, the computer or the robot may be enabled to understand and simulate the command from human. As a pre-requisite, the system should be enabled to recognize the spokesperson, who is speaking to it However, in the realistic scene, the noise from the complex environment may cause some difficulties for the system to realize this function By imitating the performance of human, we try to use the eyes of the robot to solve the problem In this research, we propose a new spokesperson detection method based on image processing The system might find and identified all the possible spokesperson around it, by detecting and recognizing the faces in the video form the cameras on the robot It might also find out the spokesperson who is speaking to it, by judging the mouth action of possible spokesperson Using eye cameras and an omni-directional camera, we tried to realize the system and some experiments were conducted to verify the new method (Keyword) Spokesperson detection / Complex communication environment / Face detection / Face verification / Mouth action judgment (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-77950117366 (Elsevier: Scopus)
243.	Changqin Quan and Fuji Ren : A blog emotion corpus for emotional expression analysis in Chinese, Computer Speech & Language, Vol.24, No.1, 726-749, 2010. (Summary) Weblogs are increasingly popular modes of communication and they are frequently used as mediums for emotional expression in the ever changing online world. This work uses blogs as object and data source for Chinese emotional expression analysis. First, a textual emotional expression space model is described, and based on this model, a relatively fine-grained annotation scheme is proposed for manual annotation of an emotion corpus. In document and paragraph levels, emotion category, emotion intensity, topic word and topic sentence are annotated. In sentence level, emotion category, emotion intensity, emotional keyword and phrase, degree word, negative word, conjunction, rhetoric, punctuation, objective or subjective, and emotion polarity are annotated. Then, using this corpus, we explore these linguistic expressions that indicate emotion in Chinese, and present a detailed data analysis on them, involving mixed emotions, independent emotion, emotion transfer, and analysis on words and rhetorics for emotional expression. (Keyword) Emotion analysis / Weblogs / Corpus annotation / Natural language processing (Link to Publication Site) ● Publication site (DOI): 10.1016/j.csl.2010.02.002 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1572261551381699456 ● Search Scopus @ Elsevier (DOI): 10.1016/j.csl.2010.02.002 (DOI: 10.1016/j.csl.2010.02.002, CiNii: 1572261551381699456)
244.	Fang Tian and Fuji Ren : Learning Relation Instances for Chinese Domain Ontology from the Web, IEEJ Transactions on Electrical and Electronic Engineering (TEEE), Vol.5, No.2, 188-194, 2010. (Summary) This paper presents a method to extract relation instances from the Internet in order to acquire knowledge that has some relations for domain ontology. We propose an ontology relation instance learning model: data sources are collected though the Web search engine and the extracted instances are constructed in Web ontology language (OWL) by Protege in Chinese. Basically, the extraction of relation instances contains syntactic patterns for filtering concepts and relevance measurement for selection of relation instances. A relevance measurement based on co-occurrence statistics is presented in this paper, which measures the semantic similarity of the measure between candidate instances and predefined domain keywords using Web search engines. In the experiment, we extract festival customs for different festival instances using relation has_custom between festival class and custom class in the Chinese festival ontology, and prove the effectiveness of our method. (Keyword) ontology learning / relation instance / relation extraction / co-occurrence statistics (Link to Publication Site) ● Publication site (DOI): 10.1002/tee.20516 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1573668926023927424 ● Search Scopus @ Elsevier (DOI): 10.1002/tee.20516 (DOI: 10.1002/tee.20516, CiNii: 1573668926023927424)
245.	Zhi Teng, Ye Liu and Fuji Ren : Create Special Domain News Collections through Summarization and Classification, IEEJ Transactions on Electrical and Electronic Engineering (TEEE), Vol.5, No.1, 56-61, 2010. (Summary) In this paper, we present a novel technique to create a special domain news collection system from really simple syndication (RSS) news sites through summarization and classification. The main aim of this research is to build a self-sufficient news collection system in disaster domain. In this news collection system, we used new strategies and algorithms to mine news from RSS sites, recognized and collected disaster news using automatic summarization and classification. The most striking dissimilarity between our study and previous work is that we use a novel summary approach to improve the classification performance. This paper discusses the effect of summarization and classification model on system performance. Results show that our method yields a better performance in this field. (Keyword) special domain collections / news / really simple syndication / summarization / classification (Link to Publication Site) ● Publication site (DOI): 10.1002/tee.20493 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1570572701280421504 ● Search Scopus @ Elsevier (DOI): 10.1002/tee.20493 (DOI: 10.1002/tee.20493, CiNii: 1570572701280421504)
246.	Seiji Tsuchiya, Eriko Yoshimura, Hirokazu Watabe, Tsukasa Kawaoka and Fuji Ren : An extraction technique of place-related words based on an association mechanism, International Journal of Knowledge Engineering and Soft Data Paradigms, Vol.2, No.1, 4-14, 2010. (Summary) We are conducting research on the development of an intelligent robot that can converse naturally with people. Humans manipulate smooth communications by retrieving, understanding and judging several common sense concepts from conversations consciously or unconsciously. In this paper, we focus on the expression of the place from such common sense concepts. We propose a technique which is able to associate the person and thing existing in the place and the event done on the place from the word expressing the place based on an association mechanism. F-measure of the place subject and place object was 88.0% and 84.3% respectively. The average F-measure of both was 86.2%. Moreover, result of proposed technique was 37.7% better than result of a traditional technique which used case frame dictionary. These results show that proposed technique was effective and the place judgement system has achieved a judgement similar to human's sense. (Link to Publication Site) ● Publication site (DOI): 10.1504/IJKESDP.2010.030463 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1504/IJKESDP.2010.030463 (DOI: 10.1504/IJKESDP.2010.030463)
247.	Hong Zhang and Fuji Ren : Chinese POS Tagging Using Restricted Maximum Entropy Model, Chinese Journal of Electronics, Vol.19, No.1, 39-42, 2010. (Summary) This paper presents Chinese Part-of-speech (POS) tagging using maximum entropy technique, in which we introduce a novel gain-driven method for feature selec-tion, then we describe the restricted training method for model learning. We test our approach on the simplified Chinese corpus of Peking University China and achieve an accuracy of 97.80% and 98.60% over fine and coarse grained tag set -a significant improvement over the existing Chi-nese POS tagger. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-77149157794 (Elsevier: Scopus)
248.	Xiao Sun, Degen Huang and Fuji Ren : Chinese New Word Detection and POS Tagging Based on DUCRF, Information : an International Interdisciplinary Journal, Vol.12, No.6, 1349-1357, 2009. (Summary) In Chinese language processing, new words are particularly problematic. It is impossible to get a complete dictionary as new words call always be created. We proposed a unified Dual-chain unequal-state CRF model to detect new words together with their part-of-speech in Chinese texts regardless of the word types such as compound words, abbreviation, person names, etc. The Dual-chain Unequal-state CRF model has two stale chains with unequal number of states. The unequal state chains could model flexible hierarchical lexical information for both Chinese new word detection and POS tagging, and also integrate complex context features like the global information. The experimental results show that the proposed method is capable of detecting even low frequency new words and their parts-of-speech synchronously with satisfactory results. (Keyword) New word detection / Semi-CRF / Dual-chain unequal-state CRF / POS tagging
249.	Ling Xia, Zhi Teng and Fuji Ren : Question Classification for Chinese Cuisine Question Answering System, IEEJ Transactions on Electrical and Electronic Engineering (TEEE), Vol.4, No.6, 689-695, 2009. (Summary) This paper presents an integrated method on question classification for Chinese cuisine question answering (QA) system. First, we exploit the domain knowledge to enrich question preprocessing, then classification features are extracted by means of domain attributes and the rule-based classifier is constructed. Support vector machine (SVM) classifier is used for secondary classification to the questions which cannot be matched with rules. A prototype system based on the proposed method has been constructed and an experiment on 453 natural language questions collected from Internet has been carried out. It achieved an accuracy of 96.22%. Result shows that a small number of linguistically motivated domain features can efficiently classify questions of Chinese cuisine QA system. (Keyword) question answering (QA) system / question classification / domain knowledge / rule-based / SVM-based (Link to Publication Site) ● Publication site (DOI): 10.1002/tee.20466 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1573668925686881536 ● Search Scopus @ Elsevier (DOI): 10.1002/tee.20466 (DOI: 10.1002/tee.20466, CiNii: 1573668925686881536)
250.	Michihiro Jinnai, Satoru Tsuge, Shingo Kuroiwa, Fuji Ren and Minoru Fukumi : New Similarity Scale to Measure the Difference in Like Patterns with Noise, International Journal of Advanced Intelligence (IJAI), Vol.1, No.1, 59-88, 2009. (Summary) A new similarity scale called the Geometric Distance, that numerically evaluates the degree of likeness between two patterns is proposed. Traditionally, the similarity scales known as the Euclidean distance and cosine similarity have been widely used to measure likeness. Traditional methods do not perform well in the presence of noise or pattern distortions. In this paper, a new mathematical model for a similarity scale is proposed which overcomes these limitations of the earlier models, while improving the overall recognition accuracy. Experiments in speech vowel recognition were carried out under various SNR levels in a variety of noisy environments. In all cases a significant improvementin recognition accuracy is demonstrated, with the improvement most pronounced in the noisiest conditions. In fact, at a SNR of 5 dB in a subway, the recognition accuracyimproved from 65% to 75% and at 20 dB SNR from 98.4% to 99.6% over the MFCC method. Numerical modeling of simple patterns is used to demonstrate the principles behind the Geometric Distance. (Keyword) Similarity measures / Distance functions / Pattern matching / Noise robust
251.	Lei Yu, Xiangyang Liu, Fuji Ren and Peilin Jiang : Learning to Classify Semantic Orientation on On-line Document, International Journal of Innovative Computing, Information and Control, Vol.5, No.12, 4637-4646, 2009. (Summary) As a result of advance in Internet technology, automatic text sentimentclassification for a large amount of on-line documents in the form of surveys or calledreviews becomes attractive. The task of sentiment classification is to construct an effectiveclassifier with the knowledge data of vocabularies semantic meaning and the relationshipsbetween the vocabularies to determine the sentiment orientation of a document. In thispaper, one method combining HowNet knowledge base with a robust supervised sentimentclassifier is proposed. It computes semantic similarity of characteristic words and phrasesby using HowNet. Sentiment features of text are divided into characteristic words andphrases, and they adopt the positive and negative terms as features of sentiment classifier.Finally in the experiment, evaluation results show the effectiveness of our method. (Keyword) Sentiment classification / Text semantic orientation / Opinion mining (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-74349124357 (Elsevier: Scopus)
252.	Peilin Jiang, Fuji Ren and Nanning Zheng : A New Approach to Data Clustering Using a Computational Visual Attention Model, International Journal of Innovative Computing, Information and Control, Vol.5, No.12, 4597-4606, 2009. (Summary) Cluster analysis plays an important role in many respects such as knowledge discovery, data mining and information retrieval. In this paper, we propose a newapproach inspired by the early vision system of the primate for data clustering. Humanbeings are able to locate key points that contains more important information in a complex scene. To realize this function, our approach uses a computational visual attentionmodel that selects and extracts salient areas in visual field by local difference features.Then the extracted salient areas in original visual field can be regarded as the clusters inthe data feature space. Without prior knowledge, this attention model based approach canidentify data clusters with arbitrary shapes at different scales. Finally our algorithm hasbeen tested in the evaluation experiments on the benchmark datasets to show its competitive performance. (Keyword) Data clustering / Bio-inspired approach / Selective attention / Saliency map (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-74349083025 (Elsevier: Scopus)
253.	Xiao Sun, Degen Huang and Fuji Ren : Chinese Lexical Analysis Based on Hybrid MMSM Model, International Journal of Innovative Computing, Information and Control, Vol.5, No.12, 4523-4530, 2009. (Summary) In this paper, we describe a scheme for Chinese word segmentation and POS tagging which integrates the character-based and word-based information in the directed graph generated by the MMSM-model. Word-level information is effective for analysis of known words, while character-level information is useful for analysis of unknown, words. A Hidden semi-CRF model is proposed for the unknown words detection. and POS tagging. The proposed Hidden semi-CRF has two state chains with unequal states which Can perform segmentation and POS tagging of unknown words simultaneously. The hybrid model was evaluated using the test data from SIGHAN-6 and achieved higher F-score than the stage-of-the-art models. (Keyword) Chinese morphological analysis / MMSM model / CRF / Hidden semi-CRF (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-74349100748 (Elsevier: Scopus)
254.	Liping Mi and Fuji Ren : Facilitative Effect of the Picture Superiority Effect During Encoding and Retrieval, Science & Technology Review, Vol.27, No.20, 80-86, 2009. (Summary) In order to investigate the picture superiority effect, we compared the ERP between picture combined word (picture-word) and pure word (word) during encoding and retrieval. During encoding, FN400 was more negative and lasted longer for picture-word than for word. Late positive component (LPC) was more positive and distributed broadly for word compared to picture-word. During retrieval, old picture-word elicited remarkably FN400 familiarity effect and parietal old/new effect compared to old word. We suggested that simultaneous image and verbal encoding of picture-word elicited better and faster recollection compared to word during the memory test. Our results demonstrated that the picture superiority effect was related to the ability of pictures enhancing encoding and facilitating recollection. (Keyword) encoding / retrieval / recognition memory / picture superiority effect / familiarity
255.	Peilin Jiang, Lei Yu and Fuji Ren : AN CLUSTERING APPROACH FOR COMPLEX EMOTION RELATED CATEGORIZATION, ICIC Express Letters, Vol.3, No.3, 265-270, 2009. (Summary) An affective computing, as a branch of artificial intelligence, attracts attention as a popular growing filed with many applications insofar as information retrieval, e-learning and human computer interaction. But until now the fine-grained theory of emotion is still a challenge. In this paper, a novel method to analyze emotion related category of contemporary Chinese. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-77953909896 (Elsevier: Scopus)
256.	Changqin Quan, Fuji Ren and Tingting He : Word Sense Indicators: Effective Feature for Chinese Word Sense Disambiguation, Information : an International Interdisciplinary Journal, Vol.12, No.5, 1157-1164, 2009. (Summary) This paper presents a statistical method to extract word sense indicators as semantic disambiguators. Word sense indicators are collected based on selecting the best seeds and retrieving collocations. The similarities are comparied between sets of sense indicators for tagging sense. Our experiments showed that one or two indicators around the ambiguous word can help to recognize its sense, and sense indicators are mainly appear in ±3 context window size in Chinese. (Keyword) Word sense disambiguation / Word sense indicators / Mutual information (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84860135597 (Elsevier: Scopus)
257.	Caixia Yuan, Fuji Ren, Xiaojie Wang and Yixin Zhong : Function Labeling for Unparsed Chinese Text, IEEJ Transactions on Electronics, Information and Systems, Vol.129, No.8, 1593-1600, 2009. (Summary) This paper presents a work of function labeling for unparsed Chinese text. Unlike other attempts that utilize the full parse trees, we propose an effective way to recognize function labels directly based on lexical information, which is easily scalable for languages that lack sufficient parsing resources. Furthermore, we investigate a general method to iteratively simplify a sentence, thus transferring complicated sentence into structurally simple pieces. By means of a sequence learning model with hidden Markov support vector machine, we achieve the best F-measure of 87.40 on the text from Penn Chinese Treebank resources - a statistically significant improvement over the existing Chinese function labeling systems. (Keyword) function labeling / lexical features / sequence learning / Chinese language processing (Link to Publication Site) ● Publication site (DOI): 10.1541/ieejeiss.129.1593 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1390282679580530944 ● Search Scopus @ Elsevier (DOI): 10.1541/ieejeiss.129.1593 (DOI: 10.1541/ieejeiss.129.1593, CiNii: 1390282679580530944)
258.	Liping Mi, Xiangyang Liu, Fuji Ren and Hideo Araki : Characteristics of Event-related Potentials in Recognition Processes of Japanese Kanji and Sentences for Chinese Bilinguals, Journal of Physiological Anthropology, Vol.28, No.4, 191-197, 2009. (Summary) This paper investigates the recognition process of Japanese kanji and sentences for Chinese bilinguals and Native Japanese speakers (NJS), by analyzing the event-related potential (ERP) differences between the two groups while they visually recognized Japanese kanji and sentences. The results showed that no significant differences were found between the two groups while they recognized Japanese kanji, but significant differences were found in the Japanese sentences condition. The results demonstrated that the neural mechanisms of recognition processes of Japanese sentences including kana between the two groups were not identical. When recognizing ambiguous sentences, Chinese bilinguals' P600 only appeared over the right frontal lobe, reflecting that syntactic integration and revision of ambiguous sentences for Chinese bilinguals was related with the right hemisphere. The results showed, for Chinese bilinguals, the difficulty of Japanese language learning was the recognition and understanding of Japanese sentences with kana, not Japanese kanji. We would like to provide a scientific learning method for Chinese bilinguals to enhance their Japanese language learning efficiency from the aspect of brain science. (Keyword) Adult / Brain / Brain Mapping / China / Evoked Potentials / Female / Humans / Japan / Language / Male / Reading / Young Adult (Link to Publication Site) ● Publication site (DOI): 10.2114/jpa2.28.191 (Link to Search Site for Scientific Articles) ● PubMed @ National Institutes of Health, US National Library of Medicine (PMID): 19652451 ● Search Scopus @ Elsevier (PMID): 19652451 ● Search Scopus @ Elsevier (DOI): 10.2114/jpa2.28.191 (DOI: 10.2114/jpa2.28.191, PubMed: 19652451)
259.	Nadira Begum, Fattah Abdel Mohamed and Fuji Ren : Automatic Text Summarization Using Support Vector Machine, International Journal of Innovative Computing, Information and Control, Vol.5, No.7, 1987-1996, 2009. (Summary) This work investigates different text features to select the best one and proposes an approach to address automatic text summarization. This approach is a trainable summarizer, which takes into account several features, including sentence position,sentence centrality, sentence resemblance to the title, sentence inclusion of name entity,sentence inclusion of numerical data, sentence relative length, Bushy path of the sentenceand aggregated similarity for each sentence to generate summaries. First we investigatethe effect of each sentence feature on the summarization task. Then we use all featuresscore function to train Support Vector Machine (SVM) in order to construct a text summarizer model. The proposed approach performance is measured at several compressionrates (CR) on a data corpus composed of 100 English articles from the domain of politics. (Keyword) Automatic summarization / Support vector machine / Text features (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-67749132539 (Elsevier: Scopus)
260.	Yun Li, Kaiyan Huang, Fuji Ren and Yixin Zhong : Wikipedia Dased Semantic Related Chinese Words Exploring and Relatedness Computing, Journal of Beijing University of Posts and Telecommunications, Vol.32, No.3, 109-112, 2009. (Summary) This paper introduces our way of finding semantic related Chinese word pairs from the open encyclopedia Wikipedia and analyzing the degree of semantic relations. Almost 50,000 structured documents are collected from Wikipedia pages. Then considering of hyperlinks and text overlaps etc., about 400,000 semantic related pairs are employed. We roughly measured the semantic relatedness using the position and frequency information in the documents. With comparing experiment on data sets with different degrees of semantic relations using some other classic algorithms, we analyze the reliability of our measures and other properties. (Keyword) Wikipedia / semantic relation / semantic relatedness
261.	Xiao Sun, Degen Huang and Fuji Ren : Chinese Lexical Analysis Based on Hidden Semi-CRF, ICIC Express Letters, An International Journal of Research and Surveys, Vol.3, No.2, 177-182, 2009. (Summary) In order to solve problems of the Chinese word segmentation and POS tagtaggingwhich are still existing in Chinese lexical analysis, a Hidden semi-CRF model, whichhas two chains of states with unequal number of states, is proposed for the Chinese lexicalanalysis. The Hidden semi-CRF detects the words together with their part-of-speech reregardlesswhether the words are in the system dictionary or not. A new-words-generatingframework is also built for training and testing, under which the definition and distridistributionof the new words conforms to the characteristic of the ones in real text. Theproposed framework enhances the performance of new words detecting and POS tagging,so that the overall precision of the system for Chinese lexical analysis could be furtherincreased. The experiment results show that the proposed method is capable of detectingeven low frequency new words, which in return increases the overall precision of Chineseword segmentation and POS tagging in Chinese lexical analysis. (Keyword) Chinese word segmentation / POS tagging / Chinese lexical analysis / Hidden semi-CRF model (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-67649541723 (Elsevier: Scopus)
262.	Ye Yang, Peilin Jiang, Seiji Tsuchiya and Fuji Ren : Effect of Using Pragmatics Information on Question Answering System of Analects of Confucius, International Journal of Innovative Computing, Information and Control, Vol.5, No.5, 1201-1212, 2009. (Summary) In general, the techniques of statistical retrieval and shallow language analysis are chiefly used in question answering(QA) systems in order to improve the accuracyof answers. But these techniques are not contributing effectively to restricted domain QAsystem of classic Chinese literature such as Analects of Confucius. This QA systemrequires to extract related verses and automatically answer the query in natural Chineselanguage about Confucius thought in the Analects of Confucius. Therefore we propose a novel method to integrate the pragmatics information with classical informationretrieval technique for QA system so as to improve retrieval efficiency. In this paper,we examined the effect of the pragmatics information on QA system of the Analectsof Confucius. According to the experiments, the pragmatics information based retrievalresults are more accurate than the one without using it. (Keyword) Pragmatics information / Utterance interpretation / Information retrieval / Question answering system / Analects of confucius (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-63849232781 (Elsevier: Scopus)
263.	Xiaoying Tai, Lidong Wang, Qin Chen, Fuji Ren and Kenji Kita : A New Method of Medical Image Retrieval based on Color-Texture Correlogram and GTI Model, International Journal of Information Technology & Decision Making, Vol.8, No.2, 239-248, 2009. (Summary) This paper presents a method for endoscopic image retrieval based on color texture correlogram and Generalized Tversky's Index (GTI) model. First we define a new image feature named color texture correlogram, which is the extension of color correlogram. The texture image extracted by texture spectrum algorithm is combined with color feature vector, and then we calculate the spatial correlation of colortexture feature vector. Similarity metric is also the key technology during domain of image retrieval, GTI model is used in medical image retrieval for similarity metric, and the technique of relevance feedback is used in the algorithm to enhance the efficiency of retrieval. Experimental results show that the method discussed in this paper is much more effective. (Link to Publication Site) ● Publication site (DOI): 10.1142/S0219622009003363 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1142/S0219622009003363 (DOI: 10.1142/S0219622009003363)
264.	Yun Li, Kaiyan Huang, Fuji Ren and Yixin Zhong : Exploring Words with Semantic Relations from Chinese Wikipedia, Information : an International Interdisciplinary Journal, Vol.12, No.2, 439-449, 2009. (Summary) This paper introduces a way of exploring words with semantic relations from Chinese Wikipedia documents. A corpus with structured documents is generated from Chinese Wikipedia pages. Then considering of the hyperlinks, text overlaps and word frequencies, word pairs with semantic relations are explored. Words can be self clustered into groups with tight semantic relations. We roughly measure the semantic relatedness with different document based algorithms and analyze the reliability of our measures in comparing experiment. (Keyword) Wikipedia / Semantic Relations
265.	Kazuyuki Matsumoto, Junko Minato and Fuji Ren : Retrieval Method of Example Sentence for Intelligent English Composition Support System, Information : an International Interdisciplinary Journal, Vol.12, No.2, 377-386, 2009. (Summary) Recently the opportunity of reading and writing in English has been greatly increasing. We focused on supporting the Japanese to write English sentence by indicating appropriate example sentences. This paper proposed a method to retrieve such target example sentences by using domain categories and keywords or directly inputting the Japanese sentence.The result of the experiment to evaluate the precision of example sentence retrieval indicated that our technique exceeded the conventional technique by more than 20%.
266.	Ye Yang, Peilin Jiang and Fuji Ren : The Effects of a Classic Self-Learning System Utilizing Pragmatics Information and Topic, Information : an International Interdisciplinary Journal, Vol.12, No.2, 359-368, 2009. (Summary) The purpose of this study is to construct a new self-learning system that supports the "Analects of Confucius" learning for Chinese learner and the "Analects of Confucius" learner. We present pragmatics and topic information to the learner. There are two roles of pragmatics and topic information. The first one is to clarify the verse semantic acid the second is to make "Analects of Confucius" contents familiar to the learner. The experiments evidenced the effectiveness of the presented pragmatics and topic information that is specific to increase enthusiasm for learning and enhance understanding of the contents. (Keyword) self-learning system / pragmatics information / enthusiasm for learning / understanding of the contents / linguistic education
267.	Ye Wu and Fuji Ren : Emotion Recognition Based on Negative Words and Pattern Matching For Chinese Negative Sentences, Information : an International Interdisciplinary Journal, Vol.12, No.2, 259-267, 2009. (Summary) Abstract Recently, emotion recognition with computer has attracted a great deal of attention to researchers for its broad applications. Emotion estimation from textual input has also become active as natural language processing (NLP) technology develops. However, when it comes to negative sentences in Chinese, the original emotion estimation may be reversed which makes obtaining correct recognition results difficult if we do not consider the effect of negative words.
268.	Hong Zhang and Fuji Ren : Negative Expression Translation for Japanese and Chinese Machine Translation System, Information : an International Interdisciplinary Journal, Vol.12, No.2, 247-257, 2009. (Summary) There are many differences between Chinese and Japanese in history, culture, life, manners and customs, therefore it is natural that there are particular words and special usage of words in two languages. It is necessary to correctly master the meaning of these particular words and then translate accurately between two languages. Because of the complex corresponding relationship in Chinese and Japanese, when building Japanese-Chinese machine translation, it is easy to introduce vagueness. Among the mistakenly translations in existing commercial translation software, most of them are caused by the negative expression in the sentence. In this paper, through analyzing the negative expression ways in Chinese and Japanese languages, we investigated the translation of Japanese-Chinese negative sentences by using the selection rules of Chinese negative words and position rules. The basic Japanese negative expression naide/(sic) has the same meaning with mei/(sic) and bie/(sic) in Chinese. When translating nakute/(sic) into Chinese, according to its negative meaning and grammatical rule, it may be translated into bu/(sic). In the current research, we discussed the general rules which are abstracted from typical examples including naide/(sic) and nakute/(sic). (Keyword) Negative expression / Japanese and Chinese / Machine Translation (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2008.4906788 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2008.4906788 (DOI: 10.1109/NLPKE.2008.4906788)
269.	Ye Yang, Seiji Tsuchiya and Fuji Ren : Construction of "Analects of Confucius" Knowledge Base Including Pragmatics Information, IEEJ Transactions on Electronics, Information and Systems, Vol.129, No.1, 133-139, 2009. (Summary) In this paper, we propose an approach of constructing the knowledge base for ``Analects of Confucius'', which aims to help the correct understanding of ``Analects of Confucius''. The content of ``Analects of Confucius'' has the characteristics that it has not been categorized by topics and always has comprehensive meanings. Thus it is necessary to build an framework to manage and build the knowledge base for it. The construction of knowledge base in the past work has been focusing on the research of the words and the shallow meaning and explicitly communicated meaning of the passages which can not be used for deeper meaning and implicitly communicated meaning. The present paper sets up an categorization system for ``Analects of Confucius'', then based on it, the knowledge base is built by using pragmatics information with reference to utterance interpretation method in pragmatics. The question answering system adopts the knowledge base of ``Analects of Confucius'' and gives an assessment of it. The results show that the combined answer with pragmatics information and modern text interpretation outperforms the answers which are extracted only from modern text by 32.2%. (Keyword) Analects of Confucius / Pragmatics / Pragmatics Information / Knowledge Base / Analects of Confucius / Pragmatics / Pragmatics Information / Knowledge Base (Link to Publication Site) ● Publication site (DOI): 10.1541/ieejeiss.129.133 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1390282679581927680 ● Search Scopus @ Elsevier (DOI): 10.1541/ieejeiss.129.133 (DOI: 10.1541/ieejeiss.129.133, CiNii: 1390282679581927680)
270.	Yu Zhang and Fuji Ren : Statistic Information and Grammatical Features Based Emotion Recognition For Chinese Split Phrases, Information : an International Interdisciplinary Journal, Vol.12, No.1, 183-191, 2009. (Summary) Emotion recognition in context is a new research issue with great significance. It can help people acquire the useful information from reviews or comments in the Internet. In Chinese context, there is a syntactic construction called split phrase that always carries emotional information, which cannot be recognized accurately by general lexical analysis. In order to find an effective way for recognizing this construction, we study the classification and calculation rules of split phrases in Chinese. In this paper, an emotion recognizing method based on the statistic information and grammatical feature is proposed and evaluated. The comparing experimental results show that the emotion recognition rate is improved efficiently. (Keyword) Emotion Recognition / Chinese Split Phrase / Emotion Classification
271.	Jiajun Yan, David B. Bracewell, Fuji Ren and Shingo Kuroiwa : Integration of Multiple Classifiers for Chinese Semantic Dependency Analysis, Electronic Notes in Theoretical Computer Science, Vol.225, No.1, 457-468, 2009. (Summary) Semantic Dependency Analysis (SDA) has extensive applications in Natural Language Processing (NLP). In this paper, an integration of multiple classifiers is presented for SDA of Chinese. A Naive Bayesian Classifier, a Decision Tree and a Maximum Entropy classifier are used in a majority wins voting scheme. A portion of the Penn Chinese Treebank was manually annotated with semantic dependency structure. Then each of the three classifiers was trained on the same training data. All three of the classifiers were used to produce candidate relations for test data and the candidate relation that had the majority vote was chosen. The proposed approach achieved an accuracy of 86% in experimentation, which shows that the proposed approach is a promising one for semantic dependency analysis of Chinese. (Link to Publication Site) ● Publication site (DOI): 10.1016/j.entcs.2008.12.092 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1016/j.entcs.2008.12.092 (DOI: 10.1016/j.entcs.2008.12.092)
272.	Manabu Sasayama, Fuji Ren and Shingo Kuroiwa : Automatic Extraction of Super-Function From Bilingual Corpus, Electronic Notes in Theoretical Computer Science, Vol.225, No.1, 329-340, 2009. (Summary) Extraction of a large Super-Function (SF) is one of the most important factor in realizing SF based machine translation. This paper presents a method to automatically extract SF from a Japanese-English bilingual corpus. The extraction process matches Japanese noun and English noun in each bilingual sentence in a bilingual corpus using a bilingual dictionary. The experimental results show that this method performs very well in automatically extracting SF for machine translation. Then, we discuss a problem of SF based machine translation from the result of the evaluation experiment using extracted SF. (Link to Publication Site) ● Publication site (DOI): 10.1016/j.entcs.2008.12.084 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1016/j.entcs.2008.12.084 (DOI: 10.1016/j.entcs.2008.12.084)
273.	Fuji Ren and Bracewell B. David : Advanced Information Retrieval, Electronic Notes in Theoretical Computer Science, Vol.225, No.1, 303-317, 2009. (Summary) In this paper we explore some of the most important areas of advanced information retrieval. In particular, we look at cross-lingual information retrieval, multimedia information retrieval and semantic-based information retrieval. Cross-lingual information retrieval deals with asking questions in one language and retrieving documents in one or more different languages. With an increasingly globalized economy, the ability to find information in other languages is becoming a necessity. Multimedia information retrieval deals with finding media other than text, i.e. music and pictures. With the explosion of digital media that is available on the Internet and present on users' computers techniques for quickly and accurately finding desired media is important. Semantic based information retrieval goes beyond classical information retrieval and uses semantic information to understand the documents and queries in order to aid retrieval. Semantic based information retrieval goes beyond standard surface information by using the concepts represented in documents and queries to improve retrieval performance. (Link to Publication Site) ● Publication site (DOI): 10.1016/j.entcs.2008.12.082 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1016/j.entcs.2008.12.082 (DOI: 10.1016/j.entcs.2008.12.082)
274.	Bracewell B. David, Jiajun Yan, Fuji Ren and Shingo Kuroiwa : Category Classification and Topic Discovery of Japanese and English News Articles, Electronic Notes in Theoretical Computer Science, Vol.225, No.1, 51-65, 2009. (Summary) This paper presents algorithms for topic analysis of news articles. Topic analysis entails category classification and topic discovery and classification. Dealing with news has special requirements that standard classification approaches typically cannot handle. The algorithms proposed in this paper are able to do online training for both category and topic classification as well as discover new topics as they arise. Both algorithms are based on a keyword extraction algorithm that is applicable to any language that has basic morphological analysis tools. As such, both the category classification and topic discovery and classification algorithms can be easily used by multiple languages. Through experimentation the algorithms are shown to have high precision and recall in tests on English and Japanese. (Link to Publication Site) ● Publication site (DOI): 10.1016/j.entcs.2008.12.066 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1016/j.entcs.2008.12.066 (DOI: 10.1016/j.entcs.2008.12.066)
275.	Fuji Ren : Affective Information Processing and Recognizing Human Emotion, Electronic Notes in Theoretical Computer Science, Vol.225, 39-50, 2009. (Summary) Information recognition and extraction of human emotions are necessary for machines to communicate smoothly with humans and to realize emotion communications. We focus on human psychological characteristics to develop general-purpose agents that can recognize human emotion and create machine emotion. We comprehensively analyze brain waves, voice sounds and picture images that represent information included in emotion elements of phonation, facial expressions, and speech usage. We analyze and estimate many statistical data based on the latest achievements of brain science and psychology in order to derive transition networks for human psychological states. We establish a speaker word model for researching computer simulation of psychological change and emotional presentation, developing emotion interface, and establishing theoretic structure and realization method of emotion communication. A new approach for recognizing human emotion based on Mental State Transition Network will be described and one emotion estimation method based on sentence pattern of emotion occurrence events will be discussed, and some new results of the project will be given. (Keyword) recognizing human emotion / emotion communication / Information recognition / recognize human emotion / create machine emotion (Link to Publication Site) ● Publication site (DOI): 10.1016/j.entcs.2008.12.065 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1016/j.entcs.2008.12.065 (DOI: 10.1016/j.entcs.2008.12.065)
276.	Kazuyuki Matsumoto, Tetsuya Tanioka, Kyoko Osaka, Kawamura Ai, Shu-ichi Ueno, Fuji Ren, Takasaka Yoichiro, Barnard Alan, Rozzano De Castro Locsin and Omori Mitsuko : Developing the Method of Server Controlled Outcomes Management and Variance Analysis, Electronic Notes in Theoretical Computer Science, Vol.225, 221-237, 2009. (Summary) This paper is to describe a way to develop the Psychoms process for mental health patient management and variance analysis system has been developed using artificial intelligence. Although it is agreed that there is a need for clinical pathway variance analysis, methods for creating a system are less well defined. The procedure and systematic process described aims to improve patients' quality of life through consistent and timely care. Ultimately, its potential influence is to assist in the improvement of quality health care services. This paper illustrates a method of outcomes management and variance analysis as the prospective development of future research. (Keyword) Outcome Management / variance analysis / nursing administration / team care / artificial intelligence (Link to Publication Site) ● Publication site (DOI): 10.1016/j.entcs.2008.12.076 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1016/j.entcs.2008.12.076 (DOI: 10.1016/j.entcs.2008.12.076)
277.	Fattah Abdel Mohamed and Fuji Ren : GA, MR, FFNN, PNN & GMM based Models for Automatic Text Summarization, Computer Speech & Language, Vol.23, No.1, 126-144, 2009. (Summary) This work proposes an approach to address the problem of improving content selection in automatic text summarization by using some statistical tools. This approach is a trainable summarizer, which takes into account several features, including sentence position, positive keyword, negative keyword, sentence centrality, sentence resemblance to the title, sentence inclusion of name entity, sentence inclusion of numerical data, sentence relative length, Bushy path of the sentence and aggregated similarity for each sentence to generate summaries. First, we investigate the effect of each sentence feature on the summarization task. Then we use all features in combination to train genetic algorithm (GA) and mathematical regression (MR) models to obtain a suitable combination of feature weights. Moreover, we use all feature parameters to train feed forward neural network (FFNN), probabilistic neural network (PNN) and Gaussian mixture model (GMM) in order to construct a text summarizer for each model. Furthermore, we use trained models by one language to test summarization performance in the other language. The proposed approach performance is measured at several compression rates on a data corpus composed of 100 Arabic political articles and 100 English religious articles. The results of the proposed approach are promising, especially the GMM approach. (Keyword) Automatic summarization / Genetic algorithm / Mathematical regression / Feed forward neural network / Probabilistic neural network (Link to Publication Site) ● Publication site (DOI): 10.1016/j.csl.2008.04.002 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1016/j.csl.2008.04.002 (DOI: 10.1016/j.csl.2008.04.002)
278.	Kyoko Osaka, Seiji Tsuchiya, Fuji Ren, Shingo Kuroiwa, Tetsuya Tanioka and Rozzano De Castro Locsin : The Technique of Emotion Recognition Based on Electroencephalogram, Information : an International Interdisciplinary Journal, Vol.11, No.1, 55-68, 2008. (Summary) We aim to develop the mechanism that is possible to sympathize with man, and we target at the thing to read feelings which man feels from the brain wave. This time, as an initial stage of the research how the subject is able to make judgments to be impressed from the brain wave is verified. Concretely, it is investigated by using electroencephalograph (EEG) that the brain is an active state when the subject own declaring to have been impressed. Three kinds of evaluation method are used for this research. One method is statistically evaluated based on the strength of potential. Other method is evaluated objective based on the place which brain waves activate. Another method is evaluated by comparing a subject's subjectivity with change of EEG. Subjects are two persons and a small number this time, and since those attributes are partial, a question remains in the justification of a result. However, it is also the fact which becomes clear from this result that a subject's impression condition can fully be judged from the activity state of brain waves.
279.	Manabu Sasayama, Shingo Kuroiwa and Fuji Ren : Extracting Date/Time Expressions in Super-Function Based Japanese-English Machine Translation, IEEJ Transactions on Electronics, Information and Systems, Vol.128, No.8, 1342-1350, 2008. (Summary) Super-Function Based Machine Translation(SFBMT) which is a type of Example-Based Machine Translation has a feature which makes it possible to expand the coverage of examples by changing nouns into variables, however, there were problems extracting entire date/time expressions containing parts-of-speech other than nouns, because only nouns/numbers were changed into variables. We describe a method for extracting date/time expressions for SFBMT. SFBMT uses noun determination rules to extract nouns and a bilingual dictionary to obtain correspondence of the extracted nouns between the source and the target languages. In this method, we add a rule to extract date/time expressions and then extract date/time expressions from a Japanese-English bilingual corpus. The evaluation results shows that the precision of this method for Japanese sentences is 96.7%, with a recall of 98.2% and the precision for English sentences is 94.7%, with a recall of 92.7%. (Keyword) date / time expression / Super-Function / machine translation / time expression / machine translation (Link to Publication Site) ● Publication site (DOI): 10.1541/ieejeiss.128.1342 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1390282679583410304 ● Summary page in Scopus @ Elsevier: 2-s2.0-72149097055 (DOI: 10.1541/ieejeiss.128.1342, CiNii: 1390282679583410304, Elsevier: Scopus)
280.	Fattah Abdel Mohamed and Fuji Ren : Sentence Alignment based on the Text Length between Punctuation Marks, Information : an International Interdisciplinary Journal, Vol.11, No.4, 445-465, 2008. (Summary) Sentence alignment based on the text length between punctuation marks \| sentence alignment; English/Arabic parallel corpus; parallel corpora; machine translation \| Parallel corpora have become an essential resource for work in multi lingual natural language processing. Sentence aligned parallel corpora are more efficient than non-aligned parallel corpora for cross language information retrieval and machine translation applications. In this paper, we present a new approach to align sentences in bilingual parallel corpora based on the text character length between successive punctuation marks. A probabilistic score is assigned to each proposed correspondence of texts, based on the scaled difference of lengths of the two texts (in characters) and the variance of this difference. Using this score, the time required for punctuation marks matching decreased and the sentence alignment accuracy increased. Using this new approach, we could achieve an error reduction of 26.5% over length based approach when applied on English-Arabic parallel documents. The sentence alignment execution time decreased to 17% of the total time required for the combined model which uses length based approach and punctuation approach combined together. Moreover, the proposed approach result outperforms Melamed and Moore's approach results. (Keyword) sentence alignment / English / Arabic parallel corpus / parallel corpora / machine translation / WEB
281.	Junko Minato, Kazuyuki Matsumoto, Fuji Ren, Seiji Tsuchiya and Shingo Kuroiwa : Evaluation of Emotion Estimation Methods Based on Statistic Features of Emotion Tagged Corpus, International Journal of Innovative Computing, Information and Control, Vol.4, No.8, 1931-1941, 2008. (Summary) Development of information technology has been increasing the chance of interaction between human and computer. Computer used to be a tool and its development had been mainly emphasized on the speed of information processing. However, by understanding not only semantic information but also ambiguous information such as emotion, computer can be a versatile partner for human that can detect emotional state of a person and can response appropriately the emotion. As a primary study of text-based emotion estimation by computer we focused on statistically analyzing the relationship between word emotion and sentence emotion based on the originally created emotion tagged corpus then propose two emotion estimation methods according to the obtained statistic features. The proposed methods are evaluated using a prototype system. (Keyword) Corpus analysis / Affective computing / Statistic analysis (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-63749121764 (Elsevier: Scopus)
282.	Fattah Abdel Mohamed and Fuji Ren : English-Arabic Proper Noun Transliteration Pairs Creation, Journal of the American Society for Information Science and Technology, Vol.59, No.10, 1675-1687, 2008. (Summary) Proper nouns may be considered the most important query words in information retrieval. If the two languages use the same alphabet, the same proper nouns can be found in either language. However, if the two languages use different alphabets, the names must be transliterated. Short vowels are not usually marked on Arabic words in almost all Arabic documents (except very important documents like the Muslim and Christian holy books). Moreover, most Arabic words have a syllable consisting of a consonant-vowel combination (CV), which means that most Arabic words contain a short or long vowel between two successive consonant letters. That makes it difficult to create English-Arabic transliteration pairs, since some English letters may not be matched with any romanized Arabic letter. In the present study, we present different approaches for extraction of transliteration proper-noun pairs from parallel corpora based on different similarity measures between the English and romanized Arabic proper nouns under consideration. The strength of our new system is that it works well for low-frequency proper noun pairs. We evaluate the new approaches presented using two different English-Arabic parallel corpora. Most of our results outperform previously published results in terms of precision, recall, and F-Measure. (Keyword) INFORMATION-RETRIEVAL / PARALLEL CORPORA / EXTRACTION / ALIGNMENT / WORDS (Link to Publication Site) ● Publication site (DOI): 10.1002/asi.20877 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1002/asi.20877 (DOI: 10.1002/asi.20877)
283.	Manabu Sasayama, Fuji Ren and Shingo Kuroiwa : Automatic Super-function Extraction for Translation of Spoken Dialogue, International Journal of Innovative Computing, Information and Control, Vol.4, No.6, 1371-1382, 2008. (Summary) Extraction of a large number of Super-Function (SF) is the most importantfactor in realizing SF based machine translation. This paper presents a method for automatic extraction of SF from a Japanese-English bilingual corpus. The extraction processuses a bilingual dictionary to match Japanese and English nouns in each sentence pair.The experimental results using a Japanese-English bilingual corpus show that this methodperforms very well in automatically extracting SF for machine translation. In addition,we evaluate the extracted SF in SF based machine translation. (Keyword) Super-function / Automatic extraction / Machine translation (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-48249094962 (Elsevier: Scopus)
284.	Liying Mi, Xin Luo and Fuji Ren : Chinese-Japanese Translation of Causative Sentences Using Super-function Based Machine Translation System, International Journal of Innovative Computing, Information and Control, Vol.4, No.4, 915-926, 2008. (Summary) Causative sentences in Japanese are a matter of affixation. In particular,the causative form takes the shape of a suffix. In Chinese, the causative form constitutes an independent word. In our previous studies on Super-Function Based MachineTranslation (SFBMT), we have found that causative sentences are very frequently usedand difficult to translate correctly, the over use of causative sentences can be dangerousas it may introduce ambiguity in the translation. In this paper, we discuss the challenges in handling Japanese causative sentences in an SFBMT system; we present ashallow method for translating causative sentences by using some fixed rules and SuperFunctions (SF). In the present research, sufficient Chinese-Japanese causative sentencepatterns have been employed as a language-database for experiments, which proves thesuggested method can effectively improve translation quality within the range under discussion. (Keyword) Causative sentence / NLP / Machine translation / SFBMT (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-48249156940 (Elsevier: Scopus)
285.	Bracewell B. David, Jiajun Yan and Fuji Ren : Single Document Keyword Extraction For Internet News Articles, International Journal of Innovative Computing, Information and Control, Vol.4, No.4, 905-914, 2008. (Summary) Keywords are a fundamental part of information retrieval (IR) and as suchthey have been studied extensively. They are used for everything from searching to describing a document. A Keyword extraction algorithm can be defined as a combinationof a keyword representation and a selection/weighting scheme. The most common selection/weighting schemes are based on collection statistics or using supervised machinelearning algorithms. In these cases, keywords can, typically, only be extracted from documents that belong to a collection or using a large amount of annotated training data. Theimportance of extracting keywords without a document collection has been gradually increasing due to the Internet. In this paper, a keyword extraction algorithm designed withnews in mind that requires neither a document collection or training data is presented.It uses noun phrases as its keyword representation and takes in document statistics toderive its weighting scheme. Through experimentation it is shown that the quality of thekeywords extracted from the proposed algorithm are better than standard algorithms forboth information retrieval and humans. (Keyword) Keyword extraction / Indexing / news / information retrieval system / Natural language processing (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-48249154566 (Elsevier: Scopus)
286.	Jiajun Yan, David B. Bracewell, Fuji Ren and Shingo Kuroiwa : The Creation of a Chinese Emotion Ontology Based on HowNet, Engineering Letters, Vol.16, No.1, 166-171, 2008. (Summary) Full comprehension of language comes about by understanding the meaning and the emotion behind the communication. Understanding the meaning of language is the goal of natural language processing and research on semantic analysis. Understanding emotion is one of the goals of affective computing. The two areas of artificial intelligence have recently come together for understanding emotion in text. In order to help in this pursuit, this paper describes a Chinese emotion ontology based on HowNet and its construction. The ontology should go a long way in helping to understand, classifiy, and recognize emotion in Chinese. The ontology created in this paper is made up of Chinese emotion predicates that can help in understanding the emotion of the actors in sentences. The ontology was semi-automatically created using a simple three step process. The final ontology has just under 5,500 verb predicates covering 113 different emotion categories. (Keyword) Natural Language Processing / Emotion Ontology / Affective Computing / Chinese
287.	David B. Bracewell, Fuji Ren and Shingo Kuroiwa : A Low Cost Machine Translation Method for Cross-Lingual Information Retrieval, Engineering Letters, Vol.16, No.1, 160-165, 2008. (Summary) In one form or another language translation is a necessary part of cross-lingual information retrieval systems. Often times this is accomplished using machine translation systems. However, machine translation systems offer low quality for their high costs. This paper proposes a machine translation method that is low cost while improving translation quality. This is done by utilizing multiple web based translation services to negate the high cost of translation. A best translation is chosen from the candidates using either consensus translation selection or statistical analysis. Which to use is determined by a heuristic rule that takes into account that most web based translation services are of similar quality and that machine translation still produces relatively poor results. By choosing the best translation the method is able to increase translation quality over the base systems, which is verified by the experimentation. (Keyword) Natural Language Processing / Statistical Analysis / Machine Translation / Cross-Lingual Information Retrieval
288.	Junko Minato, Bracewell B. David, Fuji Ren and Shingo Kuroiwa : Japanese Emotion Corpus Analysis and its Use for Automatic Emotion Word Identification, Engineering Letters, Vol.16, No.1, 172-177, 2008. (Summary) In this paper, the creation of a Japanese emotion cor- pus and its use in automatic emotion word identifcation are examined. The corpus was created by manually tagging words in just under 1,200 dialog sentences with emotion. Using the tagged corpus, statistical anal- ysis was performed to determine the characteristics of emotional expression in Japanese dialog. This type of analysis should prove benefcial for understanding how emotion is expressed and how to identify, classify, etc. emotion in Japanese. To test this theory an automatic emotion word identifcation system was built using machine learning based classifers with features taken from the statistical analysis. In total, four diferent classifers were trained and compared to a baseline dictionary approach. It was found that classifer based identifcation was able to signifcantly increase recall. (Keyword) Natural Language Processing / Statistical Analysis / Affective Computing / Corpus Creation
289.	Fattah Abdel Mohamed and Fuji Ren : Automatic Text Summarization, International Journal of Computer Science, Vol.3, No.1, 25-28, 2008. (Summary) This work proposes an approach to address automatic text summarization. This approach is a trainable summarizer, which takes into account several features, including sentence position, positive keyword, negative keyword, sentence centrality, sentence resemblance to the title, sentence inclusion of name entity, sentence inclusion of numerical data, sentence relative length, Bushy path of the sentence and aggregated similarity for each sentence to generate summaries. First we investigate the effect of each sentence feature on the summarization task. Then we use all features score function to train genetic algorithm (GA) and mathematical regression (MR) models to obtain a suitable combination of feature weights. The proposed approach performance is measured at several compression rates on a data corpus composed of 100 English religious articles. The results of the proposed approach are promising. (Keyword) Automatic Summarization / Genetic Algorithm / Mathematical Regression / Text Features
290.	Kyoko Osaka, Tetsuya Tanioka, Shuichi Ueno, Chiemi Kawanishi, Toshiko Tada, Shingo Kuroiwa and Fuji Ren : Empathetic Understanding as Caring in Nursing Using Electroencephalographic Data as Evidence, International Journal for Human Caring, Vol.12, No.1, 7-16, 2008. (Summary) We presume that the measurement of electroencephalographic (EEG) changes, those activities that are considered physiological indicators, enables an objective understanding of changes in emotions of those who have difficulty in expressing these through facial expression or physical action. Generally, EEG is used in the hospital to examine encephalopathy and brain disorder. Using an electroencephalograph device to acquire digital data we propose a method to objectively capture changes in the recognition state of people from changes in EEG activities (action potential), and a way to apply it into a clinical situation.
291.	Dapeng Yin, Min Shao, Fuji Ren and Shingo Kuroiwa : Improving Parsing of BA Sentences for Machine Translation, IEEJ Transactions on Electrical and Electronic Engineering (TEEE), Vol.3, No.1, 106-112, 2008. (Summary) The research on Chinese-Japanese machine translation has been lasting for many years, and now this research field is increasingly thoroughly refined. In practical machine translation system, the processing of a simple and short Chinese sentence has somewhat good results. However, the translation of complex long Chinese sentence still has difficulties. For example, these systems are still unable to solve the translation problem of complex BA sentences. In this article a new method of parsing of BA sentence for machine translation based on valency theory is proposed. A BA sentence is one that has a prepositional word BA. The structural character of a BA sentence is that the original verb is behind the object word. The object word after the BA preposition is used as an adverbial modifier of an active word. First, a large number of grammar items from Chinese grammar books are collected, and some elementary judgment rules are set by classifying and including the collected grammar items. Then, these judgment rules are put into use in actual Chinese language and are modified by checking their results instantly. Rules are checked and modified by using the statistical information from an actual corpus. Then, a five-segment model used for BA sentence translation is brought forward after the above mentioned analysis. Finally, we applied this proposed model into our developed machine translation system and evaluated the experimental results. It achieved a 91.3% rate of accuracy and the satisfying result verified effectiveness of our five-segment model for BA sentence translation. (Keyword) machine translation / five-segment model / Chinese / Japanese (Link to Publication Site) ● Publication site (DOI): 10.1002/tee.20241 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1571980075826810240 ● Search Scopus @ Elsevier (DOI): 10.1002/tee.20241 (DOI: 10.1002/tee.20241, CiNii: 1571980075826810240)
292.	Peilin Jiang, Hua Xiang and Fuji Ren : The Framework of Mental State Transition Analysis, Lecture Notes in Computer Science, Vol.4827, 1046-1055, 2007. (Summary) The Human Computer Interaction (HCI) Technology has emerged in the different fields in applications in computer vision and recognition systems such as virtual environment, video games, e-business and multimedia management. In this paper we propose a framework of designing the Mental State Transition (MST) of a human being or virtual character. The expressions of human emotion can be easily remarked by facial expressions, gestures, sound and other visual characteristics. But the potential MST modeling in affective data are always hidden actually. We analysis the framework of MST and employ DBNs to construct the MST networks and finally the experiment has been implemented to derive the ground truth of the data and verify the effectiveness. (Keyword) Mental State Transition / HCI / Psychological Experiment / Virtual Character (Link to Publication Site) ● Publication site (DOI): 10.1007/978-3-540-76631-5_100 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-38149112499 (DOI: 10.1007/978-3-540-76631-5_100, Elsevier: Scopus)
293.	Kazuyuki Matsumoto, Fuji Ren, Shingo Kuroiwa and Seiji Tsuchiya : Emotion Estimation Algorithm Based on Interpersonal Emotion Included in Emotional Dialogue Sentences, Lecture Notes in Computer Science, Vol.4827, 1035-1045, 2007. (Summary) Emotion recognition aims to make computer understand ambiguous information of human emotion. Recently, research of emotion recognition is actively progressing in various fields such as natural language processing, speech signal processing, image data processing or brain wave analysis. We propose a method to recognize emotion in dialogue text by using originally created Emotion Word Dictionary. The words in the dictionary are weighted according to the occurrence rates in the existing emotion expression dictionary. We also propose a method to judge the object of emotion and emotion expressivity in dialogue sentences. The experiment using 1,190 sentences proved about 80% accuracy. (Link to Publication Site) ● Publication site (DOI): 10.1007/978-3-540-76631-5_99 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-38149123913 (DOI: 10.1007/978-3-540-76631-5_99, Elsevier: Scopus)
294.	Peilin Jiang, Ran Li, Fuji Ren, Shingo Kuroiwa and Nanning Zheng : Color Features Based Speaking Detection with Hidden Markov Model in Video Sequences, Research in Computing Science, Vol.32, 374-381, 2007. (Summary) The Human Computer Interface Technology has faced challenges of understanding user's mind actively. In the ¯rst, the speak detection is a primary technique in applications of human computer interface(HCI) and other applications like surveillance system, video conferenceand multimedia data base management in computer vision and speechrecognition. This paper describes a novel method to detect speaker witha probabilistic model of behavior of speaking. After human face recognition, the especial components under the nonlinear transformation incolor space of lip represent the speci¯c mouth region and then combine the groups of coherent motions . Next the simple movements in themouth region are modeled by hidden Markov models. The experimentalresults demonstrate that the model representing speaking is e±ciencyand successful in applying to driver video surveillance system.
295.	Yu Zhang, Zhuoming Li, Fuji Ren and Shingo Kuroiwa : A Construction of Emotion Thesaurus Basing on Chinese Character and Empirical Knowledge, Research in Computing Science, Vol.32, 330-340, 2007. (Summary) There have been some studies about spoken natural language dialog, and most of them have successfully been developed within the specified domains. However, current human-computer interfaces only get the data to process their programs. Aiming at developing an affective dialog system, we have been exploring how to incorporate emotional aspects of dialog into existing dialog processing techniques. As a preliminary step toward this goal, we work on making a Chinese emotion classification model which is used to recognize the main affective attribute from a sentence or a text. Finally we have done experiments to evaluate our model.
296.	Kazuma Hara, Shingo Kuroiwa, Kouji Tanaka, Satoru Tsuge, Fuji Ren, Masami Shishibori and Kenji Kita : Acoustic Model Adaptation Using Speech Synthesis for Codec Speech Recognition, The Transactions of the Institute of Electronics, Information and Communication Engineers D, Vol.J90-D, No.9, 2541-2549, 2007. (Summary) 現在,IP電話端末から音声認識システムを利用する場合,音声データ通信時における音声圧縮・伸張(符号化)の影響より固定電話と比較して音声認識精度が低下する問題がある.これを回避するため,符号化された多量の音声データを用いて音響モデルを再学習,及び適応する手法が提案されている.しかし,再学習や適応に必要となる多量の音声データを収集することは多大な労力と時間が必要となる.そこで本論文では,音声データの収集を必要としない音響モデル適応手法を提案する.本提案手法は,認識に用いる音響モデルから適応に必要な音声データを自己生成する手法である.本論文ではこの手法を実現するため,音響モデルの各分布より音素波形を合成し適応に用いる「合成音素波形による音響モデルの分布適応法」と連続音声を合成し適応に用いる「連続合成音声を用いた音響モデル適応法」を提案する.符号化方式G723.1を用いた音声認識実験結果より,連続合成音声を用いた音響モデル適応法は適応前の音響モデルの認識精度を改善することが分かった.これらの結果より,提案手法は適応データの収集を必要とせず,符号化音声を高精度に認識する手法として有効であるといえる. (Keyword) 符号化音声認識 / 音声符号化 / HMM音声合成 / 音響モデル適応 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1520853833503954304 (CiNii: 1520853833503954304)
297.	Xin Luo, Masami Shishibori, Fuji Ren and Kenji Kita : Incorporate feature space transformation to content-based image retrieval with relevance feedback, International Journal of Innovative Computing, Information and Control, Vol.3, No.5, 1237-1250, 2007. (Summary) In recent years, the employment of feedback information to improve image retrieval precision has become a hot subject in research field. But in the traditional relevance feedback methods, both relevant and non-relevant assigned information were required for the retrieval system. For the sake of practicality and convenience, this paper assumes that users only need to label the images from the previous query as relevant, which generates a new vector as feedback information. Through the feature space transformation, it is an adjustment in the spatial resolution of the feature space. The spatial resolution around relevant samples is contracted. Meanwhile, the analysis of the user's intension together with relevant forecast of the interested objects in the database make it posiible for the less similar vectors to get closer to the query vector and thus increasing query precision. Compared with the traditional relevance feedback approach, our method is shown to obviously improve the retrieval feedback performance. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-63649127226 (Elsevier: Scopus)
298.	Shingo Kuroiwa, Satoru Tsuge, Masahiko Kita and Fuji Ren : Speaker Identification Method Using Earth Mover's Distance for CCC Speaker Recognition Evaluation 2006, International Journal of Computational Linguistics & Chinese Language Processing, Vol.12, No.3, 239-254, 2007. (Summary) In this paper, we present a non-parametric speaker identification method using Earth Movers Distance (EMD) designed for text-indepedent speaker identification and its evaluation results for CCC Speaker Recognition Evaluation 2006, organized by the Chinese Corpus Consortium (CCC) for the th International Symposium on Chinese Spoken Language Processing (ISCSLP 2006). EMD based speaker identification (EMD-IR) was originally designed to be applied to a distributed speaker identification system, in which the feature vectors are compressed by vector quantization at a terminal and sent to a server that executes a pattern matching process. In this structure, we had to train speaker models using quantized data, then we utilized a non-parametric speaker model and EMD. From the experimental results on a Japanese speech corpus, EMD-IR showed higher robustness to the quantized data than the conventional GMM technique. Moreover, it achieved higher accuracy than GMM even if the data was not quantized. Hence, we have taken the challenge of CCC Speaker Recognition Evaluation 2006 using EMD-IR. Since the identification tasks defined in the evaluation were on an open-set basis, we introduce a new speaker verification module. Evaluation results show that EMD-IR achieves 99.3 % Identification Correctness Rate in a closed-channel speaker identification task. (Keyword) Speaker Identification / Earth Movers Distance / Non-Parametric / Vector Quantization / Chinese Speech Corpus
299.	Zhi Teng, Fuji Ren and Shingo Kuroiwa : An Emotion Recognition Conversation System Based on Knowledge Database Automatic Architecture, Communications in Computer and Information Science, Vol.2, No.17, 722-731, 2007. (Summary) As conversation system it must converse with various users and have to talk about various conversations, so we have to prepare large numbers of information for conversation knowledge database, but it is so especially difficult for us. The wealth of information on the web is full and quick so those make it an attractive resource for seeking quick information to simple. Recognizing a human's emotional state can be helpful in various contexts. The most promising one is probably the man-machine interaction, the communication between an assisting robot in the household and its human user. In this paper we present an experiment named an emotion recognition conversation system based on knowledge database automatic architecture. In this exploration there are two parts different than the generic conversation system. First, our conversation system can automatic construct of knowledge database base on the Really Simple Syndication parse. Second, this system can recognize emotion from the conversation contents. The experiment showed that this method could achieve better results in practice. (Keyword) Conversation System / Conversation Knowledge Database / Emotion Recognition (Link to Publication Site) ● Publication site (DOI): 10.1007/978-3-540-74282-1_81 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1007/978-3-540-74282-1_81 (DOI: 10.1007/978-3-540-74282-1_81)
300.	Jiajun Yan, Bracewell B. David, Shingo Kuroiwa and Fuji Ren : Chinese semantic dependency analysis: Construction of a treebank and its use in classification, ACM Transactions on Speech and Language Processing, Vol.4, No.2, 1-20, 2007. (Summary) Semantic analysis is a standard tool in the Natural Language Processing (NLP) toolbox with widespread applications. In this article, we look at tagging part of the Penn Chinese Treebank with semantic dependency. Then we take this tagged data to train a maximum entropy classifier to label the semantic relations between headwords and dependents to perform semantic analysis on Chinese sentences. The classifier was able to achieve an accuracy of over 84&percnt;. We then analyze the errors in classification to determine the problems and possible solutions for this type of semantic analysis. (Keyword) Chinese / Natural language processing / maximum entropy classifiation / semantic dependency analysis (Link to Publication Site) ● Publication site (DOI): 10.1145/1233912.1233914 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1145/1233912.1233914 (DOI: 10.1145/1233912.1233914)
301.	Fattah Abdel Mohamed, Bracewell B. David, Fuji Ren and Shingo Kuroiwa : Sentence alignment using P-NNT and GMM, Computer Speech & Language, Vol.21, No.4, 594-608, 2007. (Summary) Parallel corpora have become an essential resource for work in multilingual natural language processing. However, sentence aligned parallel corpora are more efficient than non-aligned parallel corpora for cross-language information retrieval and machine translation applications. In this paper, we present two new approaches to align EnglishArabic sentences in bilingual parallel corpora based on probabilistic neural network (P-NNT) and Gaussian mixture model (GMM) classifiers. A feature vector is extracted from the text pair under consideration. This vector contains text features such as length, punctuation score, and cognate score values. A set of manually prepared training data was assigned to train the probabilistic neural network and Gaussian mixture model. Another set of data was used for testing. Using the probabilistic neural network and Gaussian mixture model approaches, we could achieve error reduction of 27% and 50%, respectively, over the length based approach when applied on a set of parallel EnglishArabic documents. In addition, the results of (P-NNT) and (GMM) outperform the results of the combined model which exploits length, punctuation and cognates in a dynamic framework. The GMM approach outperforms Melamed and Moores approaches too. Moreover these new approaches are valid for any languages pair and are quite flexible since the feature vector may contain more, less or different features, such as a lexical matching feature and Hanzi characters in JapaneseChinese texts, than the ones used in the current research. (Keyword) sentence alignment / Englisb / Arabic parallel corpus / parallel corpora / probabilistic neural network / Gaussian mixture model / SPEAKER IDENTIFICATION / MODELS / WEB (Link to Publication Site) ● Publication site (DOI): 10.1016/j.csl.2007.01.002 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1016/j.csl.2007.01.002 (DOI: 10.1016/j.csl.2007.01.002)
302.	Hua Xiang, Peilin Jiang, Shuang Xiao, Fuji Ren and Shingo Kuroiwa : A Model of Mental State Transition Network, IEEJ Transactions on Electronics, Information and Systems, Vol.127, No.3, 434-442, 2007. (Summary) Emotion is one of the most essential and basic attributes of human intelligence. Current AI (Artificial Intelligence) research is concentrating on physical components of emotion, rarely is it carried out from the view of psychology directly. Study on the model of artificial psychology is the first step in the development of human-computer interaction. As affective computing remains unpredictable, creating a reasonable mental model becomes the primary task for building a hybrid system. A pragmatic mental model is also the fundament of some key topics such as recognition and synthesis of emotions. In this paper a Mental State Transition Network Model is proposed to detect human emotions. By a series of psychological experiments, we present a new way to predict coming human's emotions depending on the various current emotional states under various stimuli. Besides, people in different genders and characters are taken into consideration in our investigation. According to the psychological experiments data derived from 200 questionnaires, a Mental State Transition Network Model for describing the transitions in distribution among the emotions and relationships between internal mental situations and external are concluded. Further more the coefficients of the mental transition network model were achieved. Comparing seven relative evaluating experiments, an average precision rate of 0.843 is achieved using a set of samples for the proposed model. (Keyword) artificial psychology / a mental state transition network / predict / psychological questionnaires (Link to Publication Site) ● Publication site (DOI): 10.1541/ieejeiss.127.434 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1390282679581622272 ● Search Scopus @ Elsevier (DOI): 10.1541/ieejeiss.127.434 (DOI: 10.1541/ieejeiss.127.434, CiNii: 1390282679581622272)
303.	Kazuyuki Matsumoto, Kenichi Mishina, Fuji Ren and Shingo Kuroiwa : Emotion Estimation Algorithm based on Emotion Occurrence Sentence Pattern, Journal of Natural Language Processing, Vol.14, No.3, 239-271, 2007. (Summary) 近年の情報処理技術の発達に伴い, 従来の情報処理の分野ではほとんど取り扱われなかった人間の感性をコンピュータで処理しようとする試みが盛んになってきた. 擬人化エージェントや感性ロボットが人のように振舞うためには, 人間が表出する感情を認識し, 自ら感情を表出することが必要である. 我々は, 感性ロボットに応用するための感情認識技術について研究している. 自然言語会話文からの感情推定を行う試みは, 多くの場合, 表面的な感情表現のみに絞つて行われてきた. しかし, 人間の発話時には常に何らかの感情が含まれていると考えられる. そこで, 本稿では, 感情語と感情生起事象文型パターンに基づいた感情推定手法を提案し, 実験システムを構築する. そして, 本手法の有効性を調べるため, シナリオ文を対象にその評価実験を行った. (Keyword) Sensibility information processing / Emotion recognition / sentience computer / natural language processing / Sensibility information processing / Emotion recognition / Sensibility computer (Link to Publication Site) ● Publication site (DOI): 10.5715/jnlp.14.3_239 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1390001204476728832 ● Search Scopus @ Elsevier (DOI): 10.5715/jnlp.14.3_239 (DOI: 10.5715/jnlp.14.3_239, CiNii: 1390001204476728832)
304.	Satoru Tsuge, Shingo Kuroiwa, Masami Shishibori, Fuji Ren and Kenji Kita : Real-timeFrequency Characteristic Normalization for Distributed Speech Recognition, Transactions of Information Processing Society of Japan, Vol.48, No.2, 900-908, 2007. (Summary) 本論文では，分散音声認識における入力系の周波数特性の際による認識率劣化を抑制する周波数特性正規化手法として，複数参照ケプストラムを用いた実時間周波数特性正規化手法を提案した． (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1050001337882493184 (CiNii: 1050001337882493184)
305.	Bracewell B. David, Fuji Ren and Shingo Kuroiwa : Mining News Sites to Create Special Domain News Collections, International Journal of Computational Intelligence, Vol.4, No.4, 56-63, 2007. (Summary) AbstractWe present a method to create special domain collections from news sites. The method only requires a single sample article as a seed. No prior corpus statistics are needed and the method is applicable to multiple languages. We examine various similarity measures and the creation of document collections for English and Japanese. The main contributions are as follows. First, the algorithm can build special domain collections from as little as one sample document. Second, unlike other algorithms it does not require a second general corpus to compute statistics. Third, in our testing the algorithm outperformed others in creating collections made up of highly relevant articles. (Keyword) Infromation Retrival / News / Special Domain Collections
306.	Shingo Kuroiwa, Yoji Mori, Masashi Takashina, Satoru Tsuge and Fuji Ren : Wind noise reduction method using the observed spectrum fine structure and esimated spectrum envelope, The Transactions of the Institute of Electronics, Information and Communication Engineers A, Vol.J90-A, No.1, 1-12, 2007. (Summary) 本論文では，パワーやスペクトル形状の変化の大きい風雑音を高精度で推定する手法を提案する．提案手法は，複数の参照用風雑音スペクトル包絡を用いフレーム毎に風雑音のスペクトル包絡を推定すると共に，当該フレームから得られる観測信号の微細構造を用い風雑音スペクトルを推定し雑音除去を行う．提案手法の評価を行うため，扇風機により発生させた風雑音を用いたシミュレーション実験を実施した．客観評価実験としてセグメンタル SNRによる評価を行った結果，提案手法はスペクトルサブトラクション(SS)法よりも大幅なセグメンタルSNRの改善を達成した．また，CMOSによる主観評価実験を行った結果，客観評価と同様に SS法と比較して大幅な改善を達成し，提案手法の有効性が示された．また実験に用いたデータを調べた結果，提案手法を用いれば，推定スペクトルと実際の雑音スペクトル間のミスマッチを低減することができ，ミュージカルノイズと呼ばれる人工的な雑音の抑制にも有効であることが分かった． (Keyword) スペクトル減算法 / 参照用スペクトル包絡 / スペクトル包絡 / スペクトル微細構造 / 風雑音 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1520853834352701696 (CiNii: 1520853834352701696)
307.	Shuang Xiao, Hua Xiang, Fuji Ren and Shingo Kuroiwa : Extracting Chinese Idiomatic Expressions from Texts to Author Reading Support Systems for Learning Chinese as Second Language, The Journal of Information and Systems in Education, Vol.5, No.1, 17-28, 2006. (Summary) Though most current researches are focusing on Chinese reading support, there is still no system that can provide a convenient support aiming at CIE (Chinese Idiomatic Expression). In this paper, we mainly propose how to help CSL (Chinese as Second Language) learners to recognize CIE in Chinese texts by using NLP (Natural Language Processing) technique. We have created a CIE database with 2,305 idiomatic expressions of contemporary Chinese. The recognition processing of CIE consists of the CIE registration, the lexical analysis, the classification of sentences, the correction of POS tags and the extraction of CIE. In our experiment of CIE recognition, we have achieved 81.65% in Recall and 94.34% in precision. According to related researches of CIE recognition and comprehension, we created a RDBMS of CIE compre-hension support resources. For helping the learners to comprehend CIEs efficiently, we have designed a Support Program which connects the results of CIE recognition and the CIE comprehension support resources. (Keyword) Chinese Idiomatic Expression / phrase extraction
308.	Fattah Abdel Mohamed, Fuji Ren and Shingo Kuroiwa : Sentence Alignment using Feed Forward Neural Network, International Journal of Neural Systems, Vol.16, No.6, 423-434, 2006. (Summary) Parallel corpora have become an essential resource for work in multi lingual natural language processing. However, sentence aligned parallel corpora are more efficient than non-aligned parallel corpora for cross language information retrieval and machine translation applications. In this paper, we present a new approach to align sentences in bilingual parallel corpora based on feed forward neural network classifier. A feature parameter vector is extracted from the text pair under consideration. This vector contains text features such as length, punctuate score, and cognate score values. A set of manually prepared training data has been assigned to train the feed forward neural network. Another set of data was used for testing. Using this new approach, we could achieve an error reduction of 60% over length based approach when applied on English Arabic parallel documents. Moreover this new approach is valid for any language pair and it is quite flexible approach since the feature parameter vector may contain more/less or different features than that we used in our system such as lexical match feature. (Keyword) Sentence alignment / English/Arabic parallel corpus / parallel corpora / machine translation (Link to Publication Site) ● Publication site (DOI): 10.1142/S0129065706000822 (Link to Search Site for Scientific Articles) ● PubMed @ National Institutes of Health, US National Library of Medicine (PMID): 17285688 ● Search Scopus @ Elsevier (PMID): 17285688 ● Search Scopus @ Elsevier (DOI): 10.1142/S0129065706000822 (DOI: 10.1142/S0129065706000822, PubMed: 17285688)
309.	Shingo Kuroiwa, Satoru Tsuge, Masahiko Kita and Fuji Ren : Evaluation of EMD-based Speaker Recognition using ISCSLP2006 Chinese Speaker Recognition Evaluation Corpus, Lecture Notes in Computer Science, Vol.4274, 539-548, 2006. (Summary) In this paper, we present the evaluation results of our proposed text-independent speaker recognition method based on the Earth Mover's Distance (EMD) using ISCSLP2006 Chinese speaker recognition evaluation corpus developed by the Chinese Corpus Consortium (CCC). The EMD based speaker recognition (EMD-SR) was originally designed to apply to a distributed speaker identification system, in which the feature vectors are compressed by vector quantization at a terminal and sent to a server that executes a pattern matching process. In this structure, we had to train speaker models using quantized data, so that we utilized a non-parametric speaker model and EMD. From the experimental results on a Japanese speech corpus, EMD-SR showed higher robustness to the quantized data than the conventional GMM technique. More- over, it has achieved higher accuracy than the GMM even if the data were not quantized. Hence, we have taken the challenge of ISCSLP2006 speaker recognition evaluation by using EMD-SR. Since the identification tasks were on an open-set basis, we introduce a new speaker verication module in this paper. Evaluation results showed that EMD-SR achieves 99.3% Identification Correctness Rate in a closed-channel speaker identication task. (Link to Publication Site) ● Publication site (DOI): 10.1007/11939993_56 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-77249093973 (DOI: 10.1007/11939993_56, Elsevier: Scopus)
310.	Fuji Ren : Chinese Text Segmentation System Using Sensitive Word Concept, Journal of Asian Information-Science-Life, Vol.2, No.3, 209-222, 2006. (Summary) The identification of words in Indo-European languages is a trivial task. However, the problem named text segmentation has been, and is still a bottleneck for various Asian languages, such as Chinese. There have been two main groups of approaches to Chinese segmentation: dictionary-based approaches and statistical approaches. However, both approaches have difficulty to deal with some Chinese texts. To address the difficulties, we propose a hybrid approach using Sensitive Word Concept to Chinese text segmentation. Sensitive words are the compound words whose syntactic category is different from those of their components. According to the segmentation, a sensitive word may play different roles, leading to significantly different syntactic structures. In this paper, we explain the concept of sensitive words and their efficacy in text segmentation firstly, then describe the hybrid approach that combines the rule-based method and the probability-based method using the concept of sensitive words. Our experimental results showed that the presented approach is able to address the text segmentation problems effectively. (Keyword) Natural Language Processing / Chinese / Text Segmentation / Sensitive Words
311.	Fuji Ren : Machine-Aided English Writing Function in MMM Projest, Journal of Asian Information-Science-Life, Vol.2, No.3, 267-282, 2006. (Summary) Multi-lingual Multi-function Multi-media intelligent system (MMM) is a big project. It is a complex intelligent system with multiple functions that can deal with multiple languages and multiple media. We have designed a new general ontology based natural language processing system referred to as Multi-lingual Multi-function Multi-media Intelligent System. This paper describes a new Machine-Aided Writing Function in the MMM. The methodology proposed in this paper can deal with any foreign language, but we focus only on how to construct a Machine-Aided English Writing system for Japanese users. With the rapid development of the internet, writing English becomes daily work for computer users all over the world. However, for most non-native users, writing English is a big challenge. To build a machine-aided system that helps non-native users not only on spelling checking and grammar checking but also on producing accurate English expressions is a challenging task. The basic idea of the method proposed in this paper is based on Super-Function (SF) means and Corpora Intelligence Technique (CIT). SF is a new concept that we present to develop multi-lingual machine translation. A prototype Machine Aiding English Writing system has been constructed based on the proposed method. Some experiments using the prototype system have been carried out and the results show the proposed method is effective. This paper discusses the SF and CIT in detail and give some new advances in the MMM project. (Keyword) Artificial Intelligence / Machine Learning / Machine Aiding Writing / Multi-lingual Multi-function Multi-media Intelligent System
312.	Fuji Ren and Hongchi Shi : An Experimental parallel machine translation system, Journal of Asian Information-Science-Life, Vol.2, No.3, 223-242, 2006. (Summary) Many machine translation systems have been developed based on different machine translation approaches. The accuracy of machine translation can be further improved by integrating different machine translation systems into one system using parallel processing techniques. We have designed and implemented an experimental parallel machine translation (PMT) system. The system consists of four independent machine translation subsystems. Each subsystem is implemented using an existing machine translation technique and has its own characteristics. When translating a sentence, each subsystem translates it independently. If more than one subsystem translates the sentence successfully, the controller chooses the best translation according to a combining algorithm implemented using statistics collected from practical translations. If no subsystem succeeds in translating the sentence, the controller partitions the sentence into sentential parts, coordinates the subsystems to translates the sentential parts, and combines the partial translation results into a translation for the whole input sentence. In this paper, we describe our experimental PMT system, present some experimental results, and outline some future research on PMT. (Keyword) parallel machine translation / natural language processing / dialogue processing / multiple translation engine
313.	Yixin Zhong and Fuji Ren : Mechanism Approach that Unifies AI, and AI with AE, WSEAS Transactions on Computers, Vol.5, No.10, 2204-2211, 2006. (Summary) Both Artificial Intelligence (AI) and Artificial Emotion (AE) have received much attention from academic as well as engineering circles. Structuralism, functionalism and behaviorism have been the three dominant approaches to the simulation of intelligence in history up to the present. All the approaches have made progress so far whereas they also, however, facing difficulties in their development. Further more, there have been no connections between the research in AI and that in AE. An attempt was thus made in the paper to propose another approach to the research in AI and AE. Different from the structuralism, functionalism and behaviorism, this approach is featured with the direct concern with the central mechanism of intelligence and emotion and is therefore termed mechanism approach. It is discovered as consequence that the transformations from information to knowledge and further to intelligence are the nucleus of the mechanism to AI and AE. A by-product that seems significant also achieved the same time that the three named approaches to AI can well be unified within the framework of mechanism approach. These discoveries, both AI and AE can successfully be simulated by mechanism approach and unifying the three approaches into harmonious one, may open up a new stage for the research in AI and AE as well as the integration of these two. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-33746961645 (Elsevier: Scopus)
314.	Kazuyuki Matsumoto, Fuji Ren and Shingo Kuroiwa : Emotion Estimation System based on Emotion Occurrence Sentence Pattern, Lecture Notes in Computer Science, Vol.4114, 902-911, 2006. (Summary) The approach of emotion estimation from the conventional text was for estimating superficial emotion expression mainly. However emotions may be included in humans utterance even if emotion expressions are not in it. In this paper, we proposed an emotion estimation algorithm for conversation sentence. We gave the rules of emotion occurrence to 1616 sentence patterns. In addition, we developed a dictionary which consisted of emotional words and emotional idioms. The proposed method can estimate emotions in a sentence by matching the sentence pattern of emotion occurrence and the rule. Furthermore, we can get two or more emotions included in the sentence by calculating emotion parameter. We constructed the experiment system based on the proposed method for evaluation. We analyzed weblog data including 253 sentences by the system, and conducted the experiment to evaluate emotion estimation accuracy. As a result, we obtained the estimation accuracy of about 60 %. (Keyword) emotion estimation / emotion occurrence sentence pattern (Link to Publication Site) ● Publication site (DOI): 10.1007/978-3-540-37275-2_113 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-33749564986 (DOI: 10.1007/978-3-540-37275-2_113, Elsevier: Scopus)
315.	Dapeng Yin, Min Shao, Peilin Jiang, Fuji Ren and Shingo Kuroiwa : Treatment of Quantifiers in Chinese-Japanese Machine Translation, Lecture Notes in Computer Science, Vol.4114, 930-935, 2006. (Summary) Quantifiers and numerals often cause mistakes in Chinese-Japanese machine translation. In this paper, an approach is proposed based on the syntactic features after classification. Using the difference in type and position of quantifiers between Chinese and Japanese, quantifier translation rules were acquired. Evaluation was conducted using the acquired translation rules. Finally, the adaptability of the experimental data was verified and the methods achieved the accuracy of 90.75%, which showed that they were effective in processing quantifiers and numerals. (Link to Publication Site) ● Publication site (DOI): 10.1007/978-3-540-37275-2_117 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-33749549943 (DOI: 10.1007/978-3-540-37275-2_117, Elsevier: Scopus)
316.	Jiajun Yan, BRACEWELL B. David, Fuji Ren and Shingo Kuroiwa : A Semantic Analyzer for Aiding Emotion Recognition in Chinese, Lecture Notes in Computer Science, Vol.4114, 893-901, 2006. (Summary) In this paper we present a semantic analyzer for aiding emotion recognition in Chinese. The analyzer uses a decision tree to assign semantic dependency relations between headwords and modifiers. It is able to achieve an accuracy of 83.5%. The semantic information is combined with rules for Chinese verbs containing emotion to describe the emotion of the people in the sentence. The rules give information on how to assign emotion to agents, receivers, etc. depending on the verb in the sentence. (Link to Publication Site) ● Publication site (DOI): 10.1007/978-3-540-37275-2_112 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-33749551489 (DOI: 10.1007/978-3-540-37275-2_112, Elsevier: Scopus)
317.	Fattah Abdel Mohamed, Fuji Ren and Shingo Kuroiwa : Text-Based English-Arabic Sentence Alignment, Lecture Notes in Computer Science, Vol.4114, 748-753, 2006. (Summary) In this paper, we present a new approach to align sentences in bilingual parallel corpora based on the use of the linguistic information of the text pair in Gaussian mixture model (GMM) classifier. A feature parameter vector is extracted from the text pair under consideration. This vector contains text features such as length, punctuation score, cognate score and a bilingual lexicon extracted from the parallel corpus under consideration. A set of manually prepared training data has been assigned to train the Gaussian mixture model. Another set of data was used for testing. Using the Gaussian mixture model approach, we could achieve error reduction of 160% over length based approach when applied on English-Arabic parallel documents. In addition, the results of (GMM) outperform the results of the combined model which exploits length, punctuation, cognate and bilingual lexicon in a dynamic framework. (Link to Publication Site) ● Publication site (DOI): 10.1007/978-3-540-37275-2_94 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-33749548834 (DOI: 10.1007/978-3-540-37275-2_94, Elsevier: Scopus)
318.	Liying MI, Xin Luo, Fuji Ren and Shingo Kuroiwa : A Rule and Super Function-based Machine Translation System for Chinese-Japanese Causative Sentences, WSEAS Transactions on Computers, Vol.5, No.9, 2122-2129, 2006. (Summary) Machine translation (MT) can be generally classified as Rule-Based Machine Translation (RBMT) or Example-Based Machine Translation (EBMT) or Statistics-Based Machine Translation (SBMT), and each has numerous problems which remain unsolved. A rule-based machine translation system is an effective way to implement a machine translation system because of its extensibility and maintainability. However, it is generally disadvantageous in processing efficiency. In this paper, we present a hybrid approach based on fixed rules and Super Functions (SF) - Based method. SF is known for its lower costs, and is applicability to common users who do not have high demand on translation quality. Our purpose is to improve the processing efficiency and the quality of machine translation. In the present research, sufficient Chinese-Japanese causative sentence patterns have been employed as a language-database for experiment, which proves the suggested method can effectively improve translation quality within the range under discussion. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-33746905825 (Elsevier: Scopus)
319.	Yu Zhang, Fuji Ren and Shingo Kuroiwa : The Validity of Metaphor in Emotion Recognizing Model, WSEAS Transactions on Computers, Vol.5, No.9, 2049-2055, 2006. (Summary) Natural language has attracted importance to some researchers working on Emotion recognizing. We have made a Chinese emotion classification model and this time we add a new element to the emotion thesaurus of this model-metaphor. Through the studying of emotion, we find the metaphor is an important way of people's communication in natural language. In this paper, firstly, we introduce every part of our emotion classification model and are focus on the new element of metaphor in our emotion thesaurus. And then we do comparative experiments in order to test our model using metaphor before and after. At last the evaluation of our model is given and our model improved through using metaphor is proved to be a more effective model in recognizing emotion from text. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-33746906607 (Elsevier: Scopus)
320.	Dapeng Yin, Min Shao, Peilin Jiang, Fuji Ren and Shingo Kuroiwa : Rule-based Translation of Quantifiers for Chinese-Japanese Machine Translation, WSEAS Transactions on Computers, Vol.5, No.9, 2031-2036, 2006. (Summary) Quantifiers and numerals often cause mistakes in Chinese-Japanese machine translation. In this paper, an approach to quantifier translation is proposed based on the syntactic features after classification. First, morphological analysis is performed on sentences extracted from a Chinese-Japanese aligned corpus, which consists of quantifiers and numerals. Next, statistical information is obtained based on the meaning of the nouns with an accompanying quantifier. Using the difference in type and position of quantifiers between Chinese and Japanese, quantifier translation rules were acquired. Evaluation was conducted by using the acquired translation rules. Finally, the adaptability of the experimental data was verified and the methods achieved an accuracy of 90.75%, showing that they were effective in processing quantifiers and numerals translation. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-33746912638 (Elsevier: Scopus)
321.	Jiajun Yan, Bracewell B. David, Fuji Ren and Shingo Kuroiwa : An Integrated System for Semantic Analysis of Chinese, WSEAS Transactions on Computers, Vol.5, No.9, 1886-1891, 2006. (Summary) Semantic dependency analysis has extensive applications in Natural Language Processing (NLP). In this paper, we present an integrated system for semantic dependency analysis of Chinese. The system is composed of 3 main modules; Syntactic analysis, headword assignment, and semantic dependency assignment. For the semantic dependency module, many classifiers are tested. Primarily, we focus on assigning headwords and determining semantic relations between headwords and modifiers. For headword assignment, we handcrafted a set of rules and achieved a very high precision of 99.54%. For determining semantic relations, we experiment with four supervised machine learning algorithms with varying features for Headword-Modifier relations assignment, and achieved precision of 84%. The experimental results show that our approaches are an effective step in developing a semantic dependency analyzer for Chinese. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-33746911088 (Elsevier: Scopus)
322.	Bracewell B. David, Fuji Ren and Shingo Kuroiwa : Building Frames of Knowledge for Causal Agents in WordNet, WSEAS Transactions on Computers, Vol.5, No.9, 1880-1885, 2006. (Summary) WordNet has become a standard tool in the NLP researcher's toolkit. While giving a plethora of information it does lack certain information that would be of great benefit. This paper examines building frames of knowledge for a subset of causal agents in WordNet. This extra knowledge can help in Question & Answering, Machine Translation, etc. After an examination of the WordNet glosses different classes were created that allow for obtaining knowledge about actions, attributes, and domains. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-33746909039 (Elsevier: Scopus)
323.	Ya Lin, Tetsuya Tanioka, Kokichi Tanihira, Fuji Ren, Toshiko Tada, Katsuyo Howard and Haruo Kobayashi : An Interactive E-learning System for Practicing Team Care by Interdisciplinary Collaboration, Kawasaki Journal of Medical Welfare, Vol.12, No.1, 37-44, 2006. (Summary) "In recent years, remote education systems using telecommunication tools such as television and the internet have been developed and applied not only in open universities and preparatory schools, but also in areas where educational resources are scarce. However, these systems do not make immediate responses to questions from the learners in real time. In addition, an interactive education system connecting the computer system and the learners who need to practice team care by interdisciplinary collaboration has yet to be developed. That is the reason why we present ""interactive e-learning system for practicing team care by interdisciplinary collaboration"" and explore the possibility of introducing such a system into practice. As regards future considerations, it is important to develop effective learning content for this system. This content promotes and reinforces the essential attitude and skills for practicing interdisciplinary team care. Determination of the effectiveness of its application depends on whether the learners can practice interdisciplinary team care virtually and apply their learning to real situations." (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1390290701475929472 (CiNii: 1390290701475929472)
324.	Shunji Mitsuyoshi, Fuji Ren, Yasuto Tanaka and Shingo Kuroiwa : Non-Verbal Voice Emotion Analysis System, International Journal of Innovative Computing, Information and Control, Vol.2, No.4, 819-830, 2006. (Summary) A non-verbal voice analysis system that recognizes, separates and ranks concurrent emotions in real time has potential application in various fields, yet such a system that could delineate emotion based solely on the sound of human voice has not been successfully demonstrated before. Here, we propose a system that recognizes human emotion by means of analyzing the fundamental frequency of human voice taken from continuous natural speech. The system detects robust fundamental frequencies and intonations by parameterizing them into pitch, power, and deviation of power. Based on these parameters, data was classified via decision-tree logic into the emotional elements of anger, joy, sorrow, and calmness. Degree of excitement was also extracted. The system was evaluated by third parties by matching the system performance to human subjective classification for each element. Results indicate that overall matching rate was 70%, and the matching rate was 86% when compared to the subjects' assessment of their own voices. Our system performance exceeded the baseline with non-verbal information, which was equivalent to human subjective assessment. (Keyword) Comparison of Subjective Evaluation / Spontaneous Emotional Speech / Conscious Emotional Speech / Emotional Parameter
325.	Bracewell B. David, Fuji Ren and Shingo Kuroiwa : Dealing with Acronyms in Biomedical Texts, Engineering Letters, Vol.13, No.2, 216-224, 2006. (Summary) Recently, there has been a growth in the amount of machine readable information pertaining to the biomedical field. With this growth comes a desire to be able to extract information, answer questions, etc. based on the information in the documents. Many of these desired tasks require sophisticated language processing algorithms, such as part-of-speech tagging, parsing, and semantic interpretation. In order to use these algorithms the text must first be cleansed of acronyms, abbreviations, and misspellings. In this paper we look at identifying, expanding, and disambiguating acronyms in biomedical texts. We present an integrated system that combines previously used methods for dealing with acronyms and Natural Language Processing techniques in new way for a new domain. The result is an integrated system that achieves a high precision and recall. We break the task up into three modular steps: Identification, Expansion, and Disambiguation. During identification, each word is examined to determine if it is an acronym or not. For this,a hybrid approach that is composed of a Naive Bayesian classifier and a set of handcrafted rules is used. We are able to achieve results of 99.96% accuracy with a small training set. During the expansion step, a list of possible meanings for the words determined to be acronyms is created. We break the expansion up into two categories, local and global expansion. For local expansion we use windowing and longest common subsequence to generate the possible expansions. Global expansion requires an acronym database to retrieve the possible expansions. (Keyword) Acronyms / Text Cleansing / Bioinformatics
326.	Shuang Xiao, Hua Xiang, Fuji Ren and Shingo Kuroiwa : A CIE Extraction Syatem for CSL Learners, International Journal of Computer Science and Network Security, Vol.6, No.7A, 152-162, 2006. (Summary) Summary It is obliged to provide an effective reading support system for CSL (Chinese as Second Language) learners, for recognition and comprehension of CIE (Chinese Idiomatic Expression) in Chinese text are very difficult for them. Though most current research are focusing on Chinese reading support, there is still no perfect system that can provide a convenient support aiming at CIE. In this paper, we mainly propose how to help CSL learners recognize and comprehend CIE. We have created a CIE database with 2,305 idiomatic expressions of contemporary Chinese. At the same time we have analyzed the basic structures and using forms of these CIE. By the analysis we have presented an extraction approach which based on rules and characters of these CIE. In our extraction experiment of CCE, the recall achieved 81.65% and the precision achieved 94.34%.
327.	Haiqing Hu, Peilin Jiang, Fuji Ren and Shingo Kuroiwa : A New Question Answering System for Chinese Restricted Domain, IEICE Transactions on Information and Systems, Vol.E89-D, No.6, 1848-1859, 2006. (Summary) In this paper, we propose the construction of a web-based Question Answering (QA) system for restricted domain, which combines three resource information databases for the retrieval mechanism, including a Question&Answer database, a special domain documents database and the web resource retrieved by Google search engine. We describe a new retrieval technique of integrating a probabilistic technique based on OkapiBM25 and a semantic analysis which based on the ontology of HowNet knowledge base and a special domain HowNet created for the restricted domain. Furthermore, we provide a method of question expansion by computing word semantic similarity. The system is first developed for a middle-size domain of sightseeing information. The experiments proved the efficiency of our method for restricted domain and it is feasible to transfer to other domains expediently using the proposed method. (Keyword) question answering system / Web-based / semantic similarit / restricted domain / Chinese (Link to Publication Site) ● Publication site (DOI): 10.1093/ietisy/e89-d.6.1848 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1574231877326703488 ● Search Scopus @ Elsevier (DOI): 10.1093/ietisy/e89-d.6.1848 (DOI: 10.1093/ietisy/e89-d.6.1848, CiNii: 1574231877326703488)
328.	Hua Xiang, Shuang Xiao, Fuji Ren and Shingo Kuroiwa : A Mind Model for an Affecitive Computer, International Journal of Computer Science and Network Security, Vol.6, No.6, 62-69, 2006. (Summary) A pragmatic emotional model is one of obligatory subjects for building a humanoid computer. This paper presents a conception of a Mental State Transition Network Model using psychological research for reference [1]. The ongoing work proposes a novel approach to detect human emotions. According to Pluchiks basic emotional classification, we defined nine basic emotional states and carried out a series of psychological investigations [2]. By the results of experiments we provide a new way to predict coming humans emotions depending on the various currents emotional states under various reinforcements. By means of statistic data derived from 227 questionnaires, the transitions in distribution among the emotions and relationships between internal mental situations and external stimuli are concluded. The high precision achieved in our evaluating experiments shows the model is helping in recognition and synthesis of human emotion.
329.	Zhong Zhang, Horoshi Toda, Hisanaga Fujiwara and Fuji Ren : Translation Invariant RI-spling Wavelet and Its Application on DE-noising, International Journal of Information Technology & Decision Making, Vol.5, No.2, 353-378, 2006. (Summary) Wavelet Shrinkage using DWT has been widely used in de-noising although DWT has a translation variance problem. In this study, we solve this problem by using the translation invariant DWT. For this purpose, we propose a new complex wavelet, the Real-Imaginary Spline Wavelet (RI-Spline wavelet). We also propose the Coherent Dual-Tree algorithm for the RI-Spline wavelet and extend it to the 2-Dimensional. Then we apply this translation invariant RI-Spline wavelet for translation invariant de-noising. Experimental results show that our method, when applied to ECG data, the medical image and the textile surface inspection can obtain better de-noising results than that of conventional Wavelet Shrinkage. (Keyword) Complex wavelet transform / de-noising / wavelet shrinkage / translation invariance / image (Link to Publication Site) ● Publication site (DOI): 10.1142/S0219622006001976 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1142/S0219622006001976 (DOI: 10.1142/S0219622006001976)
330.	Fattah Abdel Mohamed, Fuji Ren and Shingo Kuroiwa : Effects of Phoneme Type and Frequency on Distributed Speaker Identification and Verification, IEICE Transactions on Information and Systems, Vol.E89-D, No.5, 1712-1719, 2006. (Summary) In the European Telecommunication Standards Institute (ETSI), Distributed Speech Recognition (DSR) front-end, the distortion added due to feature compression on the front end side increases the variance flooring effect, which in turn increases the identification error rate. The penalty incurred in reducing the bit rate is the degradation in speaker recognition performance. In this paper, we present a nontraditional solution for the previously mentioned problem. To reduce the bit rate, a speech signal is segmented at the client, and the most effective phonemes (determined according to their type and frequency) for speaker recognition are selected and sent to the server. Speaker recognition occurs at the server. Applying this approach to YOHO corpus, we achieved an identification error rate (ER) of 0.05% using an average segment of 20.4% for a testing utterance in a speaker identification task. We also achieved an equal error rate (EER) of 0.42% using an average segment of 15.1% for a testing utterance in a speaker verification task. (Keyword) Distributed speaker recognition / speaker recognition / speaker identification / speaker verification / wireless communications (Link to Publication Site) ● Publication site (DOI): 10.1093/ietisy/e89-d.5.1712 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1573387452395837184 ● Search Scopus @ Elsevier (DOI): 10.1093/ietisy/e89-d.5.1712 (DOI: 10.1093/ietisy/e89-d.5.1712, CiNii: 1573387452395837184)
331.	Zhao Xin, Fuji Ren and Shingo Kuroiwa : Translation of Japanese Noun Compounds at Super-Function Based MT System, IEEJ Transactions on Electronics, Information and Systems, Vol.126, No.5, 645-653, 2006. (Summary) The translation of noun compounds has become a major issue in Machine Translation (MT) due to their frequency of occurrence and high productivity. In our previous studies on Super-Function Based Machine Translation (SFBMT), we have found that noun compounds are very frequently used and difficult to be translated correctly, the overgeneration of noun compounds can be dangerous as it may introduce ambiguity in the translation. In this paper, we discuss the challenges in handling Japanese noun compounds in an SFBMT system, we present a shallow method for translating noun compounds by using a word level translation dictionary and target language monolingual corpus. (Keyword) machine translation / compound noun / super-function (Link to Publication Site) ● Publication site (DOI): 10.1541/ieejeiss.126.645 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1390282679582065920 ● Search Scopus @ Elsevier (DOI): 10.1541/ieejeiss.126.645 (DOI: 10.1541/ieejeiss.126.645, CiNii: 1390282679582065920)
332.	Yu Zhang, Zhuoming Li, Fuji Ren and Shingo Kuroiwa : A Preliminary Research of Chinese Emotion Classification Model, Research in Computing Science, Vol.19, 95-106, 2006. (Summary) There have been some studies about spoken natural language dialog, and most of them have successfully been developed within the specified domains. However, current human-computer interfaces only get the data to process their programs. Aiming at developing an affective dialog system, we have been exploring how to incorporate emotional aspects of dialog into existing dialog processing techniques. As a preliminary step toward this goal, we work on making a Chinese emotion classification model which is used to recognize the main affective attribute from a sentence or a text. Finally we have done experiments to evaluate our model.
333.	Shuang Xiao, Hua Xiang, Fuji Ren and Shingo Kuroiwa : The Recognition system of CCE for CSL Learners, Research in Computing Science, Vol.19, 49-61, 2006. (Summary) CSL (Chinese as Second Language) learners need relevant reading support because recognition of CCE (Chinese Conventional Expression) is a difficulty for them. In this paper, we mainly propose how to help CSL learners recognize CCE in Chinese text. We have created a CCE data-base with 2,305 conventional expressions of contemporary Chinese. At the same time we have analyzed the basic structures and application forms of these 2,305 conventional expressions. By the analysis we have presented an extraction approach which based on rules and characters of these CCE. In our extraction experiment of CCE, the recall achieved 81.65% and the precision achieved 94.34%.
334.	Fattah Abdel Mohamed, Fuji Ren and Shingo Kuroiwa : Stemming to Improve Translation Lexicon Creation form Bitexts, Information Processing & Management, Vol.42, No.4, 1003-1016, 2006. (Summary) Arabic is a morphologically rich language that presents significant challenges to many natural language processing applications because a word often conveys complex meanings decomposable into several morphemes (i.e. prefix, stem, suffix). By segmenting words into morphemes, we could improve the performance of English/Arabic translation pair's extraction from parallel texts. This paper describes two algorithms and their combination to automatically extract an English/Arabic bilingual dictionary from parallel texts that exist in the Internet archive after using an Arabic light stemmer as a preprocessing step. Before using the Arabic light stemmer, the total system precision and recall were 88.6% and 81.5% respectively, then the system precision an recall increased to 91.6% and 82.6% respectively after applying the Arabic light stemmer on the Arabic documents. The algorithms have certain variables which values can be changed to control the system precision and recall. Like most of the systems do, the accuracy of our system is directly proportional to the number of sentence pairs used. However our system is able to extract translation pairs from a very small parallel corpus. This new system can extract translations from only two sentences in one language and two sentences in the other language if the requirements of the system accomplished. Moreover, this system is able to extract word pairs that are translation of each others, synonyms and the explanation of the word in the other language as well. By controlling the system variables, we could achieve 100% precision for the output bilingual dictionary with a small recall. (Keyword) Multilingual dictionaries / English/Arabic translation / Multilingual thesaurus / Stemming (Link to Publication Site) ● Publication site (DOI): 10.1016/j.ipm.2005.07.002 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1016/j.ipm.2005.07.002 (DOI: 10.1016/j.ipm.2005.07.002)
335.	Shingo Kuroiwa, Yoshiyuki Umeda, Satoru Tsuge and Fuji Ren : Nonparametric Speaker Recognition Method using Earth Mover's Distance, IEICE Transactions on Information and Systems, Vol.E89-D, No.3, 1074-1081, 2006. (Summary) In this paper, we propose a distributed speaker recognition method using a nonparametric speaker model and Earth Mover's Distance (EMD). In distributed speaker recognition, the quantized feature vectors are sent to a server. The Gaussian mixture model (GMM), the traditional method used for speaker recognition, is trained using the maximum likelihood approach. However, it is difficult to fit continuous density functions to quantized data. To overcome this problem, the proposed method represents each speaker model with a speaker-dependent VQ code histogram designed by registered feature vectors and directly calculates the distance between the histograms of speaker models and testing quantized feature vectors. To measure the distance between each speaker model and testing data, we use EMD which can calculate the distance between histograms with different bins. We conducted text-independent speaker identification experiments using the proposed method. Compared to results using the traditional GMM, the proposed method yielded relative error reductions of 32% for quantized data. (Keyword) distributed speaker recognition / speaker identification / nonparametric / Earth Mover's Distance (Link to Publication Site) ● Publication site (DOI): 10.1093/ietisy/e89-d.3.1074 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1572261551842025344 ● Search Scopus @ Elsevier (DOI): 10.1093/ietisy/e89-d.3.1074 (DOI: 10.1093/ietisy/e89-d.3.1074, CiNii: 1572261551842025344)
336.	Shingo Kuroiwa, Satoru Tsuge, Koji Tanaka, Kazuma Hara and Fuji Ren : Acoustic Model Adaptation for Codec Speech based on Learning-by-Doing Concept, Advances in Natural Language Processing Research in Computing Science, Vol.18, 105-114, 2006. (Summary) Recently, personal digital assistants like cellular phones are shifting to IP terminals. The encoding-decoding process utilized for transmitting over IP networks deteriorates the quality of speech data. This deterioration causes degradation in speech recognition performance. Acoustic model adaptations can improve recognition performance. However,the conventional adaptation methods usually require a large amount of adaptation data. In this paper, we propse a novel acoustic model adaptation technique that generates speaker-independent HMM for the target environment based on the learning-by-doing concept. The proposedmethod uses HMM-based speech synthesis to generate adaptation datafrom the acoustic model of HMM-based speech recognizer, and consequently does not require any speech data for adaptation. By using thegenerated data after coding, the acoustic model is adapted to codecspeech. Experimental results on G.723.1 codec speech recognition showthat the proposed method improves speech recognition performance. Arelative word error rate reduction of approximately 12% was observed. (Keyword) Speech Recognition / Model Adaptation / Codec Speech / Speech Synthesis / Learning-by-Doing
337.	Satoru Tsuge, Masami Shishibori, Fuji Ren, Kenji Kita and Shingo Kuroiwa : Specific Speaker's Japanese Speech Corpus over Long and Short Time Periods, Advances in Natural Language Processing Research in Computing Science, Vol.18, 115-124, 2006. (Summary) We have been collecting the Japanese speech corpus for investigating the relationship between intra-speaker speech variability and speech recognition performance. In this paper, we introduce our speech corpus. Our corpus consists of six speakers speech data. Each speaker read specific utterance sets three times a day, once a week. Using a specific female speakers speech data in this corpus, we conduct speech recognition experiments for investigating the relationship between intra-speaker speech variability and speech recognition performance. Experimental results show that the variability ofrecognition performance over different days is larger than variability of recognition performance within a day.
338.	Fattah Abdel Mohamed, Fuji Ren, Shingo Kuroiwa, Satoru Tsuge and Ippei Fukuda : Phoneme Based Speaker Modeling to Improve Speaker Recognition System, Information, Vol.9, No.1, 135-147, 2006. (Summary) The most common approach to speaker recognition today is the use of global Gaussian Mixture Models (GMM) which ignores knowledge of the underlying phonetic content of the speech, so it does not take advantage of all available information. In this paper we investigate the phoneme effect on speaker recognition system. We found that some phonemes have strong effect on speaker identification. By segmenting the most effective phonemes for speaker recognition task from a speaker utterance, we could decrease the system complexity and the recognition time. Moreover, this technique is very useful to speed up the authentication process through wire/wireless communication systems. This paper is concerned with improving the performance of speaker recognition systems in two areas: decreasing the identification error rate and decreasing the utterance part required for identification task. We have applied several approaches on YOHO corpus; most of these approaches outperformed previously published results on the speaker identification task. Two of our approaches could achieve 0.0% error rate and one of these two approaches used only an average segment of 13% of the testing utterance for recognition. (Keyword) speaker recognition / phoneme effect on speaker recognition system / phonetic content
339.	Fattah Abdel Mohamed, Fuji Ren and Shingo Kuroiwa : Probabilistic Neural Network Based English-Arabic Sentence Alignment, Lecture Notes in Computer Science, Vol.3878, 97-100, 2006. (Summary) In this paper, we present a new approach to align sentences in bilingual parallel corpora based on a probabilistic neural network (P-NNT) classifier. A feature parameter vector is extracted from the text pair under consideration. This vector contains text features such as length, punctuation score, and cognate score values. A set of manually aligned training data was used to train the probabilistic neural network. Another set of data was used for testing. Using the probabilistic neural network approach, an error reduction of 27% was achieved over the length based approach when applied on English-Arabic parallel documents. (Keyword) Sentence Alignment / Probabilistic Neural Network / English / Arabic / bilingual parallel corpora (Link to Publication Site) ● Publication site (DOI): 10.1007/11671299_11 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-33745583239 (DOI: 10.1007/11671299_11, Elsevier: Scopus)
340.	Haiqing Hu, Fuji Ren, Shingo Kuroiwa and Shuwu Zhang : A Question Answering System on Special Domain and the Implementation of Speech Interface, Lecture Notes in Computer Science, Vol.3878, 458-469, 2006. (Summary) In this paper, we propose a construction of Question Answering(QA) system, which synthesizes the answers retrieval from the frequent asked questions database and documents database, based on special domain about sightseeing information. A speech interface for the special domain was implemented along with the text interface, using an acoustic model HMM, a pronunciation lexicon, and a language model FSN on the basis of the feature of Chinese sentence patterns. We consider the synthetic model based on statistic VSM and shallow language analysis for sightseeing information. Experimental results showed high accuracy can be achieved for the special domain and the speech interface is available for frequently asked questions about sightseeing information. (Keyword) Question Answering System / Similarity Computing / Special Domain / speech recognition / Chinese (Link to Publication Site) ● Publication site (DOI): 10.1007/11671299_48 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-33745546622 (DOI: 10.1007/11671299_48, Elsevier: Scopus)
341.	Mohamed Fattah, Fuji Ren and Shingo Kuroiwa : Speaker Recognition for Wire/Wireless Communication Systems, The International Arab Journal of Infromation Technology, Vol.3, No.1, 28-34, 2006. (Summary) Recently data communication spread to the mobile wireless world. The complexity of medium and large speech & speaker recognition systems are beyond the memory and computational resources of the small portable devices. Moreover the most common approach to speaker recognition today is the use of global Gaussian mixture models (GMM) which ignores knowledge of the underlying phonetic content of the speech, so it does not take advantage of all available information. In this paper we address the solution of these two problems by investigating the phoneme effect on speaker recognition system. We used YOHO database for speaker identification task. We found that some phonemes have strong effect on speaker identification. Segmenting the most effective phoneme for speaker recognition task from a speaker utterance and send this phoneme only through the wireless communication system will decrease the complexity of medium and speed up the authentication process though mobile communication system. We have applied different approaches on YOHO corpus, several of these approaches were able outperform previously published results on the speaker ID task. One of our approaches could achieve 0.7% error rate by using only an average segment of 4.45% of the testing utterance for recognition.
342.	Shingo Kuroiwa, Kuniyoshi Kobayashi, Satoru Tsuge and Fuji Ren : Packet Loss Concealment Algorithm using Speech Recognition and Synthesis, The Journal of the Acoustical Society of Japan, Vol.62, No.1, 3-11, 2006. (Summary) 近年, VoIP技術の発展により, 急速にIP電話が普及しつつある．IP電話の本質的な問題として(特に無線区間がある場合), パケット損失による音声品質の劣化が挙げられる．この問題を解決するため, 音声認識技術と音声合成技術を用いた音声途切れ補間手法を提案する．提案手法は, (1) Missing Feature Theoryに基づく音声認識により, 途切れ区間の音素片列を前後の言語情報及び音響情報から推定し, (2) 推定した音素片列に基づきHMM音声合成を行い, 途切れ区間の音声波形を生成し補間する．本手法で補間した特定女性話者の音声を用いて主観評価実験と客観評価実験を行い, 提案手法の有効性を示す． (Keyword) Missing feature theory / Packet loss / Speech recognition / HMM-based speech synthesis / Speech quality (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1390282681544565888 (CiNii: 1390282681544565888)
343.	Fuji Ren and Kang Yen : Estimating the Minimum Entropy of Chinese and Japanese Languages, International Journal of Information Technology & Decision Making, Vol.4, No.4, 679-689, 2005. (Summary) The study of minimum entropy of a natural language has been an interesting research subject. For English a great progress has been made, but a few reports on other languages have been found in literature. Based on two hypotheses on conservation of information quantity, we proposed a method, which can be used to estimate the minimum entropy of characters in natural languages. With a large quantity of translation corpus, this method enables us to estimate the minimum entropy without calculating the probability. Besides, as the scale of translation corpus increases, the fluctuation of the ratio between character quantities in any two languages becomes negligible. In this paper, we apply this method to the study of two languages of a large character total, Japanese and Chinese. (Keyword) Minimum Entropy / Conservation of Information Quantity / Natural Language (Link to Publication Site) ● Publication site (DOI): 10.1142/S0219622005001702 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-33746253133 (DOI: 10.1142/S0219622005001702, Elsevier: Scopus)
344.	Peilin Jiang, Hua Xiang, Fuji Ren and Shingo Kuroiwa : An Advanced Mental State Transtion Network and Psychological Experiments, Lecture Notes in Computer Science, Vol.3824, No.1, 1026-1035, 2005. (Summary) The study of human-computer interaction is now the mostpopular research domain overall computer science and psychology science. The most of essential issues recently focus on not only the information about the physical computing but also the affective computing.The emotion states of human being can dramatically affect their actions.It is important for a computer to understand what the people feel at thetime. In this paper, we propose a novel method to predict the future emotion state of person depending on the current emotion state and affectivefactors by an advanced mental state transition network. The psychological experiment with about 100 participants has been done to obtainthe structure and the coefficients of the model. The test experiment alsohas been done to certificate the prediction validity of this model. (Link to Publication Site) ● Publication site (DOI): 10.1007/11596356_102 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-33744964947 (DOI: 10.1007/11596356_102, Elsevier: Scopus)
345.	Qiong Liu, Xin Lu, Fuji Ren and Shingo Kuroiwa : Automatic Stock Market Forecasting and Correlative Natural Language Generation, International Journal of Information, Vol.8, No.6, 881-890, 2005. (Summary) Time-series forecasting is an important research area in several domains. Recently, neural networks have been very successfully applied in time series to improve multivariate prediction ability. Several neural network model have already been developed for the market prediction. Some are applied to predicting the change of future interest rate and exchange rate; some are applied to recognizing certain price patterns that are characteristic of future price changes. This paper presents a neural network model for technical analysis of stock market, and its application to a buying and selling timing prediction system for stock index of Japan. This paper also describes a natural language generation system using Extensible Super-Function (ESF) to express prediction information of TOPIX in natural language for non-expert users. This system has evolved to be one of the most comprehensive grammars of English for prediction expressions.
346.	Ya Lin, Zhi Teng, Bracewell B. David, Fuji Ren and Shingo Kuroiwa : Development of a Multimedia Bidirectional Learning System Environment, International Journal of Information, Vol.8, No.6, 871-879, 2005. (Summary) During the last decade, multimedia learning system environments, using television and internet for instance, have been widely deployed not only in open universities, preparatory schools and technical exchange, but also in areas where the education system is underdeveloped. However, these learning systems are not capable of bidirectional learning. In this paper, we describe a bidirectional multimedia learning system environment. The bidirectional learning system environment is not the traditional e-Learning system, but is one that incorporates a surveillant system and a QA (Question&Answer) system. The surveillant system does not only track and record a learner's study status, but also prompts those who are not earnest at all times using a pattern recognition system. The QA system uses speech recognition and is used to identify and answer questions proposed by a learner. This system solves the problem of a lack of bidirectionality and control by a learner in the former e-Learning education systems. (Keyword) e-Learning system / Surveillant System / QA system / speech recognition system
347.	Qiong Liu, Xin Lu, Fuji Ren and Shingo Kuroiwa : XML based extended Super-Function schema in Knowledge Representation, Journal of Research on Computing Science, Vol.16, 3-12, 2005. (Summary) In recent years, the usual knowledge representation (KR) problem in artificial intelligence is how to automatically represent andtransform different kinds of knowledge using one kind of schema. Especially this problem focuses on representing formal knowledge in naturallanguage for human understanding. For this purpose, this paper proposesan extended super-function (ESF) schema to build a novel KR system.This system can translate the data of stock market or other fields intothe corresponding natural language expression automatically. Moreover,this system benefits from XML techniques which formalize and constructall information using the common Web rules to realize the ESF schema.
348.	Shingo Kuroiwa, Satoru Tsuge, Masami Shishibori, Fuji Ren and Kenji Kita : Simple PCAを用いたベクトル空間情報検索モデルの次元削減, IEEJ Transactions on Electronics, Information and Systems, Vol.125, No.11, 1773-1779, 2005. (Summary) In this paper, we propose to use the Simple Principal Component Analysis (SPCA) for dimensionality reduction of the vector space information retrieval model. The SPCA algorithm is a data-oriented fast method which does not require the computation of the variance-covariance matrix. In SPCA, principal components are estimated iteratively so we also propose a criteria to determine the convergence. The optimum number of iterations for each principal component can be determined using the criteria. Experimentally, we show that the SPCA-based method offers improvement over the conventional SVD-based method despite its small amount of computation. This advantage of SPCA can be attributed to its iterative procedure which is similar to clustering methods such as $k$-means clustering. On the other hand, the proposed method which orthogonalizes the basis vectors also achieved much higher accuracy than the conventional random projection method based on $k$-means clustering. (Keyword) 情報検索 / ベクトル空間モデル / 次元削減 / Simple PCA / クラスタリング / Information retrieval / Vector Space Model / Dimensionality Reduction / Simple PCA / clustering (Link to Publication Site) ● Publication site (DOI): 10.1541/ieejeiss.125.1773 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1390282679580608000 ● Search Scopus @ Elsevier (DOI): 10.1541/ieejeiss.125.1773 (DOI: 10.1541/ieejeiss.125.1773, CiNii: 1390282679580608000)
349.	Bracewell B. David and Fuji Ren : A Memory and Search Hybrid Genetic Algorithm for non-Stationary Environments with Repetitive Natures, Research on Computing Science, Vol.14, No.1, 35-46, 2005. (Summary) We look at combining a search-based and memory-based approach creating a hybrid GA to solve problems with non-stationary environments. In particular, the memory search hybrid GA (MSHGA) we present is well suited to deal with non-stationary environments that are repetitive in nature, i.e. different problem landscapes are repeatedly seen. The MSHGA is capable of recalling candidate solutions for previously seen problem landscapes. This ability coupled with the search based technique of random immigrants causes the MSHGA to outperform the SGA and random immigrants GA in our experiments.
350.	Li Taihao and Fuji Ren : Super-Function based Ubiquitous Chinese Vocabulary Learning, INFORMATION, Vol.8, No.4, 547-556, 2005. (Summary) As intercourse and business between Japan and China increases, more Japanese go to China for traveling or for business. Overcoming the language obstacle is becoming an important project. This paper describes a ubiquitous Chinese language learning system using super-function (SF) in PDA. SF is a function that shows the correspondence between original and target language sentence patterns in machine translation. In his project, we focused on Chinese language learning to provide learners with the right information at the right time in the right way.
351.	Zhao Xin, Fuji Ren and Shingo Kuroiwa : Automatic Translation of Compound Nouns in the Japanese-Chinese Machine Translation System SFBMT, INFORMATION, Vol.8, No.3, 405-413, 2005. (Summary) The translation of compound nouns is a major issue in Machine Translation due to their frequency of occurrence and high productivity. Several aspects of compound nouns make them particularly difficult to be handled in a system performing automatic translation. In this paper, we discuss the challenges in automatic translating Japanese compound nouns into Chinese in the Super-Function based machine translation (SFBMT) system to address this issue. In our previous studies on SFBMT, we have found that there are many problems caused by compound nouns,the overgeneration of compound nouns can be dangerous as it may introduce ambiguity in the translation. To solve those problems, in this paper we present a shallow method for translating Japanese compound nouns into Chinese using a word level translation dictionary and target language monolingual corpus. (Keyword) machine translation / compound noun / super-function
352.	胡海青, Fuji Ren and Shingo Kuroiwa : Chinese Automatic Question Answering System of Specific-Domain Based on Vector Space Model, IEEJ Transactions on Electronics, Information and Systems, Vol.125, No.5, 698-706, 2005. (Summary) In order to meet the demand to acquire necessary information efficiently from large electronic text, the Question and Answering (QA) technology to show a clear reply automatically to a question asked in the users natural language has widely attracted attention in recent years. Although the research of QA system in China is later than that in western countries and Japan, it has attracted more and more attention recently. In this paper, we propose a Question-Answering construction, which synthesizes the answer retrieval to the questions asked most frequently based on common knowledge, and the document retrieval concerning sightseeing information. In order to improve reply accuracy, one must consider the synthetic model based on statistic VSM and the shallow semantic analysis, and the domain is limited to sightseeing information. A Chinese QA system about sightseeing based on the proposed method has been built. The result is obtained by evaluation experiments, where high accuracy can be achieved when the results of retrieval were regarded as correct, if the correct answer appeared among those of the top three resemblance degree. The experiments proved the efficiency of our method and it is feasible to develop Question-Answering technology based on this method. (Keyword) Question Answering System / Information Retrieval / Vector Space Model / Chinese / Vector Space Model / Chinese (Link to Publication Site) ● Publication site (DOI): 10.1541/ieejeiss.125.698 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1390282679582232960 ● Search Scopus @ Elsevier (DOI): 10.1541/ieejeiss.125.698 (DOI: 10.1541/ieejeiss.125.698, CiNii: 1390282679582232960)
353.	Tetsuya Tanioka, 高坂要一郎, 永峰勲, Fuji Ren, 片岡睦子, 中屋公子, Toshiko Tada, 大坂京子, Hiroki Moriguchi, Fumiko Hashimoto, Yasuko Matsushita, Ruriko Yamashita, 伊藤奈織子, 小田典子, 木曽利恵, 延和佳奈 and 山口友紀子 : 統合失調症用のクリニカルパス及びアウトカム管理の確認項目の作成と重要性の検討, a·la·care, Vol.24, No.1, 103-116, 2005. (Summary) 近年，クリニカルパスはケアを改善するために用いられるようになった．この研究の目的は統合失調症用のためのCPを開発することである．その主要な焦点は，①ノーマライゼーションの理念に基づいたチームケアを実践すること，②CPと連動した患者アウトカム管理用の重要な品質管理項目を明確にすることである．アウトカム管理を病院で行うことによって，患者·家族のQuality of Lifeの向上，良好な費用対効果，医療者の満足度の向上，入院期間の短縮等の効果が得られる．筆者らは，(Interdisciplinary Collaborative Team Care Model: ICTCM)を2000年に導入し，1999年の平均在院日数205．7日(1994年の平均在院日数675．5日)を2004年には155．2日に短縮した病院において，学際的なケア提供者と事務責任者を調査対象として，聞き取り調査を行い，統合失調症用のCPとアウトカム管理項目を作成した． (Keyword) schizophrenia / Normalization / Outcome management / Clinical path / Team care (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1572543025723225856 (CiNii: 1572543025723225856)
354.	Fuji Ren : Automatic abstracting important sentences, International Journal of Information Technology & Decision Making, Vol.4, No.1, 141-152, 2005. (Summary) Being increasingly popular, the Internet greatly changes our lives. We can conveniently receive and send information via the Internet. With the information explosion on the Web, it is becoming crucial to develop means to automatically extract important sentences from the Web articles. In this paper, we propose a method which uses both statistical and structural information for sentence extraction. In addition, following the analysis of human's extractions, several heuristic rules are added to filter out non-important sentences and to prevent similar sentences from being extracted. Our experimental results proved the effectiveness of these means. In particular, once the heuristic rules being added, a significant improvement has been observed. (Keyword) Automatic Extraction of Important Sentence / statistical information / structural feature / web (Link to Publication Site) ● Publication site (DOI): 10.1142/S0219622005001428 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1142/S0219622005001428 (DOI: 10.1142/S0219622005001428)
355.	Wang Xiaojie and Fuji Ren : Chinese-Japanese Clause Alignment, Lecture Notes in Computer Science, Vol.3406, No.1, 400-412, 2005. (Summary) Bi-text alignment is useful to many Natural Language Processing tasks such as machine translation, bilingual lexicography and word sense disambiguation. This paper presents a Chinese-Japanese alignment at the level of clause. After describing some characteristics in Chinese-Japanese bilingual texts, we first investigate some statistical properties of Chinese-Japanese bilingual corpus, including the correlation test of text lengths between two languages and the distribution test of length ratio data. We then pay more attention to n-m(n>1 or m>1) alignment modes which are prone to mismatch. We propose a similarity measure based on Hanzi characters information for these kinds of alignment mode. By using dynamic programming, we combine statistical information and Hanzi character information to find the overall least cost in aligning. Experiments show our algorithm can achieve good alignment accuracy. (Keyword) Parallel corpus / alignment / Natural Language Processing (Link to Publication Site) ● Publication site (DOI): 10.1007/978-3-540-30586-6_43 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-24344442070 (DOI: 10.1007/978-3-540-30586-6_43, Elsevier: Scopus)
356.	Hu Haiqing, Fuji Ren and Shingo Kuroiwa : Chinese Automatic Question Answering System for Sightseeing Tourists, International Journal of Information, Vol.8, No.1, 177-186, 2005. (Summary) In this paper, we propose a Question-Answering (QA) construction, which synthesizes the answers retrieved to the questions most frequently asked, based on common knowledge and text knowledge about sightseeing information. In order to improve replies more accurately, one must consider the synthetic model based on statistic VSM and the shallow semantic analysis, so that the domain is only limited to sightseeing information. Finally, the result is obtained by evaluation experiments, where high accuracy can be achieved when the results of retrieval are seen as correct, if the correct answer has appeared up to the third higher rank which sorts the value of the resembling degree. The experiments proved the efficiency in our method and it is feasible to use this method to develop Question-Answering technology. (Keyword) Question Answering System / Sightseeing Tpurists / text knowledge / vector space model
357.	Fattah Abdel Mohamed, Fuji Ren and Shingo Kuroiwa : Adaptive Threshold Parameters for Bilingual Dictionary Extraction from the Internet Archive, International Journal of Information, Vol.8, No.1, 165-176, 2005. (Summary) Parallel corpus is a very important tool to construct a good machine translation system or make any natural language processing research for cross language information retrieval. Internet archive is a good source of parallel documents of different languages. In order to construct a good parallel corpus from the Internet archive Bilingual dictionary is a must. This paper describes two algorithms to automatically extract an English/ Arabic bilingual dictionary from parallel texts that exist in the Internet archive. Each algorithm has certain parameters which values could be changed to increase the system precision and the number of extracted translation pairs. The system should preferably be useful for many different language pairs. Like most of t! he systems done, the accuracy of our system is directly proportional to the number of sentence pairs used. But our system is able to extract translation pairs from a very small parallel corpus. This new system can extract translations from only two sentences in one language and two sentences in the other language if the requirements of the system accomplished. Moreover, this system is able to extract word pairs that are translation of each other and the explanation of the word in the other language as well. We applied the system on English / Arabic parallel documents and the results were good. By controlling the system parameters, we could achieve very high precision for the output bilingual dictionary. (Keyword) Parallel corpus / machine translation system / Bilingual dictionary
358.	Fuji Ren : 人間感情の認知と機械感情の創生ができる感情インターフェース, International Journal of Information, Vol.8, No.1, 7-20, 2005. (Summary) 本論文では，人間感情の認知及び機械感情の創生モジュールを提案し，特に感情インターフェースを実現するための心的状態遷移ネットワークの構築手法を提案する．具体的に言えば，人間の心的な特性に着目し，脳波，音声，画像を用いて話者の発声の感情要素，話者の顔の表情，及び話者の言葉使いに含まれる情報を総合的に解析し，脳科学と心理学の最新研究成果を基に，大量の統計データを解析·推定し，人間の心的状態遷移ネットワークを導出する． (Keyword) 人間感情の認知 / 機械感情の創生 / 感情インターフェース / 心的状態遷移ネットワーク
359.	Zhao Xin, Fuji Ren and Vob Stefan : A Super-Function Based Japanese-Chinese Machine Translation System for Business Users, Lecture Notes in Computer Science, Vol.3265, No.1, 272-281, 2004. (Summary) In this paper, a Japanese-Chinese machine translation system using the so-called Super-Function (SF) approach is presented. A SF is a functional relation mapping sentences from one language to another. The core of the system uses the SF approach to translate without going through syntactic and semantic analysis as many MT systems usually do. Our work focuses on business users for whom MT often is a great help if they need an immediate idea of the content of texts like e-mail messages, reports, web pages, or business letters. In this paper, we aim at performing MT between Japanese and Chinese to translate business letters by the SF based technique. (Keyword) Super-Function / business letters / machine translation system (Link to Publication Site) ● Publication site (DOI): 10.1007/978-3-540-30194-3_30 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-35048827905 (DOI: 10.1007/978-3-540-30194-3_30, Elsevier: Scopus)
360.	Nasiff-Hada G., Yen K., Caballero A. and Fuji Ren : Collective Behavior of Distributed Systems in Manufacturing Environments, Engineering Mechanics, Vol.11, No.4, 1-10, 2004. (Summary) We study the Hogg-Huberman model used for resource allocation problem and extend the results of 2 agents and 2 resources to L agents and L resources. It has been shown that when processes can choose among many possible strategies, which collaborating in the solution of tasks, the dynamics can lead to oscillations and chaos. In this paper a first-order exponential filter has been proposed to improve the response. Another solution based on the average of the payoff functions for every resource shared by agents can also achieve a stable response and hold a good convergence time. (Keyword) resource allocation problem / Hogg-Huberman model / solution of tasks
361.	Fuji Ren : An Algorithm for Determining DingYu Structural Particle DE, Computational Linguistics and Intelligent Text Processing, Vol.2945, No.1, 338-349, 2004. (Summary) Nowadays a practical Japanese-Chinese machine translation system based on translation rules has been implemented. However, the current system lacks the ability for resolving the problem mentioned above. To resolve this problem, this paper presents an algorithm for determining DingYu structural particle using the grammar knowledge and statistical information. We first collect a large number of grammar items from Chinese grammar books, and obtain some elementary judgment rules by classifying and inducing the collected grammar items. Then we put these judgment rules into use in actual Chinese language, and modify the rules by checking their results instantly. Lastly we check and modify the rules by using the statistical information from a actual corpus. An experiment system based on the proposed algorithm has been constructed and an experiment is carried out. The result shows the effectiveness of the presented method. (Keyword) Japanese-Chinese machine translation / translation rule / structural particle (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-35048859843 (Elsevier: Scopus)
362.	Fuji Ren and Shunji Mitsuyoshi : To Understand and Create the Emotion and Sensitivity, International Journal of Information, Vol.6, No.5, 547-556, 2003. (Summary) This paper presents a new machine called sentience system computer to understand and create emotions and sensitivities. According to the interpretation in the many-worlds quantum theory, the spontaneous intuition of human can be defined as what is produced by interference from the self multiple worlds resulted from all piles of self-history. If the total of the interferences from the multiple worlds other than human self is already fixed, it will be possible to control the interferences. This paper describes the principles and practices of SSC, the basic spontaneity type algorithm. (Keyword) understand emotions / create emotions / sentience system computer
363.	Fuji Ren and Li Shigang : Automatic Derivation of Programming Using Domain Knowledge, International Journal of Information, Vol.6, No.2, 179-186, 2003. (Summary) ユーザにより自然言語記述で書かれた要求文をプログラムに変換するのを支援するシステムがあれば，ユーザはプログラムを簡単に得ることができる．一方，コンピュータによる自然言語理解が困難であり，しかも自然言語記述には要求が過不足なく反映されるとは限らない．人間にとっては十分な表現であってもコンピュータではその意図を把握することは難しい面もある．本論文ではこのような問題を解決するため，予め用意した領域知識により自然言語文の曖昧性の解消手法，要求細分類化によりプログラムベースの検索方法，さらに，人間の部分介入によるプログラムの生成方法を提案する．現在，このシステムはまだ初歩的段階であるが，算数文書だ問題のプログラムを生成する実験では，本研究で提案した方法が有効であると考える．
364.	Tai Xiaoying, Fuji Ren and Kenji Kita : Improvement of vector space information retrieval by using long-term relevance feedback, Asian-Information-Science-Life, Vol.2, No.1, 83-96, 2003. (Summary) This paper proposes a new method to improve information retrieval performance of the vector space model (VSM) by long term preservation of user-supplied relevance information in the system. The proposed method incorporates user's relevance feedback information and information of original documents similarities into the retrieval model that is build by using a sequence of linear transformations. The results of our experiments show that the proposed method has better retrieval performance and provides an approach that enables preservation of user-supplied information in the system.
365.	Zong Chengqing and Fuji Ren : Chinese Utterance Segmentation in Spoken Language Translation, Computational Linguistics and Intelligent Text Processing, Vol.LNCS2588, 516-525, 2003. (Summary) This paper presents an approach to segmenting Chinese utterances for a spoken language translation system in which Chinese speech is the source input. We propose this approach as a supplement to the function of sentence boundary detection in speech recognition, in order to identify the boundaries of simple sentences and fixed expressions within the speech recognition results of a Chinese input utterance. In this approach, the plausible boundaries of split units are determined using several methods, including keyword detection, pattern matching, and syntactic analysis. Preliminary experimental results have shown that this approach is helpful in improving the performance of SLT systems. (Keyword) Chinese speech / spoken language translation system / speech recognition
366.	Fuji Ren, Mitsuyoshi Shunji, Yen Kang, Zong Chengqing and Zhu Hongbing : An Estimate Method of the Minimum Entropy of Natural Languages, Computational Linguistics and Intelligent Text Processing, Vol.LNCS2588, 382-392, 2003. (Summary) The study of minimum entropy of a natural language has been an interesting research subject. For English a great progress has been made, but a few reports on other languages have been found in literature. Based on two hypotheses on conservation of information quantity, we proposed a method, which can be used to estimate the minimum entropy of characters in natural languages. With a large quantity of translation corpus, this method enables us to estimate the minimum entropy without calculating the probability. Besides, as the scale of translation corpus increases, the fluctuation of the ratio between character quantities in any two languages becomes negligible. In this paper, we apply this method to the study of two languages of a large character total, Japanese and Chinese. (Keyword) minimum entropy of a natural language / translation corpus / information quantity
367.	Tai Xiaoying, Fuji Ren and Kenji Kita : An information retrieval model based on vector space method by supervised learning, Information Processing & Management, Vol.38, No.6, 749-764, 2002. (Summary) This paper proposes a method to improve retrieval performance of the vector space model in part by utilizing user-supplied information of those documents that are relevant to the query in question. In addition to the user's relevance feedback information, information such as original document similarities is incorporated into the retrieval model, which is built by using a sequence of linear transformations. High-dimensional and sparse vectors are then reduced by singular value decomposition and transformed into a low-dimensional vector space, namely the space representing the latent semantic meanings of words. The method has been tested with two test collections, the Medline collection and the Cranfield collection. (Keyword) information retrieval / document / feedback information / vector space model (Link to Publication Site) ● Publication site (DOI): 10.1016/S0306-4573(01)00053-X (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1573950401491463680 ● Search Scopus @ Elsevier (DOI): 10.1016/S0306-4573(01)00053-X (DOI: 10.1016/S0306-4573(01)00053-X, CiNii: 1573950401491463680)
368.	Shi Hongchi, Zhao Yunxin, Zhuang Xinhua and Fuji Ren : GAM:A General Auto-associative Memory Model, IEICE Transactions on Information and Systems, Vol.E85-D, No.7, 1153-1164, 2002. (Summary) This paper attempts to establish a theory for a general auto-associative memory model. We start by defining a new concept called supporting function to replace the concept of energy function. As known, the energy function relies on the assumption of symmetric interconnection weights, which is used in the conventional Hopfield auto-associative memory, but not evidenced in any biological memories. We then formulate the information retrieving process as a dynamic system by making use of the supporting function and derive the attraction or asymptotic stability condition and the condition for convergence of an arbitrary state to a desired state. The latter represents a key from variant samples. Finally, we develop an algorithm to train the system to recover desired states from their variant samples. The effectiveness of the recalling and learning algorithms is experimentally demonstrated. (Keyword) auto-associative memory model / supporting function / energy function (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1574231877209057280 ● Summary page in Scopus @ Elsevier: 2-s2.0-0036630295 (CiNii: 1574231877209057280, Elsevier: Scopus)
369.	Fuji Ren and Shingo Kuroiwa : New Advances on Multi-Lingual Multi-Function Multi-Media Intelligent System, International Journal of Asian Information-Science-Life, Vol.1, No.1, 83-92, 2002. (Summary) A large variety of information processing applications deal with natural language texts. Many such applications require extracting and processing the meanings of the natural language texts, in addition to processing their syntactic forms. In order to extract meanings from texts and manipulate them, a natural language processing system must have a significant amount of knowledge about the world and the domain of discourse. However, different kinds of knowledge are required for different languages, for different functions, and for different media. In this paper, we design a new general ontology based natural language processing system referred to as Multi-lingual Multi-function Multi-media intelligent system. It is a complex system with multiple functions that can deal with multiple languages and multiple media. The general ontology consists of a static layer and a dynamic layer, and it provides a real world knowledge model for the natural language processing system. This paper presents the concept of MMM and hoe to build MMM system for real applications, and describes some new advances on the project. (Keyword) information processing application / knowledge / Multi-Lingual Multi-Function Multi-Media Intelligent System
370.	台暁英, Masami Shishibori, Kenji Kita and Fuji Ren : 長期的適合性フィードバックによるベクトル空間モデルの精度改善, INFORMATION, Vol.5, No.2, 255-265, 2002. (Summary) 本論文では，ユーザからのフィードバック情報を，長期的にベクトル空間モデルに基づく検索システムに残す方法を提案する．提案するモデルでは，検索精度を高めるため，ユーザからの適合性の判定結果だけではなく，文書間距離などの情報も検索モデルに組み入れ，線形変換によりベクトル空間検索モデルを構築する．その後，ベクトル空間モデルの高次元行列を特異値分解により縮退し，低次元のベクトル空間，つまり索引語と文書の潜在的な意味構造を表した意味空間に変換する．提案手法により，実験システムを構築し，二つのテストコレクションを用いて，評価実験を行った．本論文で提案した手法の有効性を確かめることができた． (Keyword) ベクトル空間モデル / 文書間距離 / フィードバック情報 / 高次元行列
371.	Zhu Hongbing, Sun Ningping, Sasaki Mamore, Eguchi Kei, Tabata Toru and Fuji Ren : A Boltzmann Machine with Non-rejective Move, IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, Vol.E85, No.6, 1229-1235, 2002. (Summary) It has been one open and significant topic for real-time applications to enhance the processing-speed of Boltzmann machines for long time. One effective way of solution of this problem is the augmentation of probability of neurons' state move. In this paper, a novel method, called a rejectionless method, was proposed and introduced into the Boltzmann machines for this augmentation. This method has a feature of independence on the ratio of neurons' state move. The efficiency of this method for speed-up was confirmed with the experiments of TSP and graph problem. (Keyword) real-time applications / Boltzmann machine / neurons' state move / graph problem (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1572261552263496832 ● Summary page in Scopus @ Elsevier: 2-s2.0-0036614763 (CiNii: 1572261552263496832, Elsevier: Scopus)
372.	Li Shigang and Fuji Ren : Realizing Face-to-Face Interaction by View-Based Tracking, International Journal of Information Technology & Decision Making, Vol.1, No.2, 331-347, 2002. (Summary) In this paper, we propose a method of realizing face-to-face interaction by view-based tracking between a human and a mobile robot. Although individuals can be recognized easily by observing frontal faces, it is difficult to do it from profiles of face. To cope with this problem, our mobile robot first finds face-like areas based upon the skin color distribution which is made from real image samples. Second, a facial pattern in the image is found and its direction relative to the robot is estimated in terms of the memorized views. Finally, the mobile robot moves to the front of the face according to the face direction which tracking the face by using visual feedback based upon active vision approach. (Keyword) mobile robot / face-to-face interaction / tracking (Link to Publication Site) ● Publication site (DOI): 10.1142/S021962200200018X (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1142/S021962200200018X (DOI: 10.1142/S021962200200018X)
373.	Fuji Ren and Shi Hongchi : A Multi-Engine Translation Approach to Machine Translation, International Journal of Information Technology & Decision Making, Vol.1, No.2, 349-366, 2002. (Summary) One of the most difficult problems in dialogue machine translation is to correctly translate irregular expressions in natural conversations such as ungrammatical, incomplete, or ill-formed sentences. However, most existing machine translation systems reject utterances including irregular expressions. In this paper, we present a dialogue machine translation approach based on a cooperative distributed natural language processing model to attack the complex machine translation problem. In this approach, different types of translation processors are used in the analysis of the original language and the generation of the target language. The idea of combining multiple machine translation engines provides a new effective way to increase the success rate and quality of dialogue machine translation. Experiments show that the approach presented in this paper is effective in implementation of robust dialogue machine translation systems. (Keyword) dialogue machine translation / multiple machine translation engines / irregular expressions (Link to Publication Site) ● Publication site (DOI): 10.1142/S0219622002000191 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1142/S0219622002000191 (DOI: 10.1142/S0219622002000191)
374.	Fuji Ren and Fan Lixin : Translation Rule and Empirical Knowledge in Machine Translation, International Journal of INFORMATION, Vol.5, No.1, 81-91, 2002. (Summary) This paper proposes a method for machine translation based on the translation rules which are extracted from very large corpora. Unlike in traditional approaches, corpora is separated from translation system. This means that we first acquire translation rules from corpora, and then construct translation system using these translation rules. This approach keeps the desirable feature of the example-based method, but does not increase the cost of time and memory. Experiments we made show that the proposed method in this paper is effective for the implement of robust translation and the development of practical machine translation system. (Keyword) translation rule / corpora / Empirical Knowledge
375.	Li Shigang and Fuji Ren : {Making a Local Map of Indoor Environments by Swiveling a Camera and a Sonar, INFORMATION, Vol.4, No.2, 223-232, 2001. (Summary) This paper proposes a method of making a local map of indoor environments by swiveling a camera and a sonar. By swiveling a camera, an omni-directional panoramic image of high azimuth angle solution can be obtained. Meanwhile, RCDs corresponding to boundary edges and walls can be obtained by swiveling a sonar. Since many vertical lines exist in indoor environments, a local map of indoor environments can be acquired based upon position of a vertical line in space. This paper proposes the method of fusing and gives the experimental results in a real indoor environment. (Keyword) local map / camera / real indoor environment
376.	Fuji Ren : A Hybird Approach of Text Segmentation Based on Sensitive Word Concept for NLP, Computational Linguistics and Intelligent Text Processing, Vol.2004, No.1, 375-388, 2001. (Summary) Natural language processing, such as checking and correction of texts, machine translation, and information retrieval, usually starts from words. The identification of words in Indo-European languages is a trivial work. However, this problem named text segmentation has been, and is still a bottleneck for various Asian languages, such as Chinese. There have been two main groups of approaches to Chinese segmentation: dictionary based approaches and statistical approaches. However, both approaches have difficulty to deal with some Chinese text. To address the difficulties, we propose a hybrid approach using sensitive word concept to Chinese text segmentation. In this paper, we explain the concept of sensitive words and their efficacy in text segmentation firstly, then describe the hybrid approach that combines the rule based method and the probability based method using the concept of sensitive words. Our experimental results showed that the presented approach is able to address the text segmentation problems effectively. (Keyword) Text Segmentation / machine translation / Sensitive Word
377.	Fuji Ren and Li Shigang : Dialogue Machine Translation based upon Parallel Translation Engines and Face Image Processing, INFORMATION, Vol.3, No.4, 521-531, 2000. (Summary) 会話文の機械翻訳はテキストの翻訳より難しい．特に会話文では多くの非文法的な現象が多い．このような会話文の特徴に着目して，並列翻訳エンジンと顔イメージ情報を利用した新しい翻訳方法を提案した．言葉だけ会話文の意味解釈が同定できない場合，話者の顔表情により判別する新しいアプローチであるが，会話文機械翻訳システムの構築に有効であると考える． (Keyword) 会話文機械翻訳 / 顔表情 / 並列翻訳エンジン
378.	Fuji Ren and Nie Jianyun : Sensitive Words and their application in Chinese Language Processing, Lecture Notes in Artificial Intelligence, Vol.1902, No.1, 121-126, 2000. (Summary) 機械翻訳システムを構築する際，できるだけ長い語を基本単位として処理するのが望ましい．長い単位の語は複合語と呼ぶ．しかしながら，複合語において一部の複合語は一つの単位で処理できない．本論文では，大量のデータの解析を行い，敏感語という自然言語の概念を提案した．即ち，複合語を敏感語と非敏感語に分類することができる．本論文で中国語の敏感語およびその言語処理への応用手法を提案した． (Keyword) 機械翻訳 / 敏感語 / 複合語
379.	Zhou Qiang and Fuji Ren : Acquisitions and Applications of Structure Preference Relations in Chainese, Natural Language Engineering, Vol.6, No.2, 163-181, 2000. (Summary) In this paper, we propose a new ambiguity representation scheme, structure preference relation (SPR), which consists of useful quantitative distribution information for ambiguous structures. Two automatic acquisition algorithms, the first acquired from a Treebank, and the second acquired from raw texts, are introduced, and some experimental results which prove the availability of the algorithms are also given. Finally, we introduce some SPR applications in linguistics and natural language processing, such as preference-based parsing and the discovery of representative ambiguous structures, and propose some future research directions. (Keyword) ambiguity representation scheme / structure preference relation / automatic acquisition algorithm
380.	Fuji Ren and 財満康通 : 自然言語記述からプログラムへの生成を支援するシステムの提案, HCU-IS, Vol.99, No.012, 1-11, 1999. (Summary) In this paper we describe AIDPG, an interactive prototype system, which derives computer programs from their natural language descriptions. AIDPG shows how to analyze natural language, solves ambiguities using know ledges, and generates program. AIDPG consists of a natural language input model (NLI-Model), a natural language analysis model(NLA-Model), a program generation model(PGG-Model) and a human machine interface control model(HMC-Model). The PGG model has three sub-models, a program structural manage sub-model, a data structural and type manage sub-model, and a program base manage sub-model. We used arithmetic problems which descripted in Japanese to pass AIDPG and got their run-possible C programs. Although AIDPG is basic currently we got a significant result.
381.	Zhang Jianping and Fuji Ren : An Optimal Combinations Approach for Cost Estimation Models of Management Information System, INFORMATION, Vol.2, No.4, 471-478, 1999. (Summary) 管理情報システムのコスト評価について，システム生命周期モデルや推定コストモデルなどが提案された．しかしながら，このような単一のモデルを用いると，性能が不安定となり，適応される範疇が限定される．本論文では管理情報システムのコスト評価に関する最適な組み合せアプローチを提案した．その基本的なアイディアとしては，単一の手法ではそれぞれ長所もあれば短所もあるが，幾つかの単一の手法を組み込んで最適な融合方法を見つけることが挙げられる．さらに，幾つかの実際の実例を用い，実験と評価を行い，提案したアプローチの有効性を確認することができた． (Keyword) 管理情報システム / システム生命周期モデル / 推定コストモデル / コスト評価
382.	Nie Jian-Yun and Fuji Ren : Chinese Information Retrieval: Using Characters or Words?, Information Processing & Management, Vol.35, No.4, 443-462, 1999. (Summary) 現代の情報検索の欲求は，情報の爆発を前題としており，知的情報検索の課題は，この多様な内容を持つ膨大な文書の中から，多様な利用者が必要とする情報を，いかに容易かつ的確に提供するかである．和文を対象とした情報検索では，従来単語を分割してから，単語単位で検索方法を開発したが，中国語で書かれた文章に対する情報検索においては従来の方法が役には立たず，多くの問題が残されている．例えば，中国語の形態素解析の結果の正確率が高くないので，単語の同定が困難である．本論文では中国語を例とする情報検索では，単語か漢字かを利用する状況を分析して新しい情報検索手法を提案し，いろいろな実験を行った． (Keyword) 報検索 / 単語単位 / 中国語
383.	Jiang Shengping and Fuji Ren : Visualization and Synthesizing of Ocean Waves, INFORMATION, Vol.2, No.2, 243-248, 1999. (Summary) 本論文では目に見えるようにする海洋波の総合的な合成手法を提案した．シミュレーション結果から本手法の有効性を確認することができた．いくつかの応用例を記述した． (Keyword) 海洋波 / simulation
384.	Fuji Ren : T+文法の開発及びコーパスの収集, HCU-IS, Vol.99, No.6, 1-83, 1999. (Summary) This paper present a new grammar called T+ grammar. T+ grammar tries to use the theme-type characteristics of Chinese and Japanese. We present a new method for Chinese-Japanese Machine Translation (CJMT) using the theme-type characteristics. We consider that Chinese and Japanese are theme-type languages, whose basic syntactic structure are Theme-Subject-Predicate-Object and Theme-Subject-Object-Predicate, respectively. This paper discusses the translation relationships between the deep structure and the surface structures of the syntax.
385.	Fuji Ren, Fan Lixin and Nie Jian-Yun : On Rule Extraction from Translation Examples in Machine Translation, Communications of COLIPS, Vol.9, No.1, 19-39, 1999. (Summary) 高性能の機械翻訳システムを実現するためには，いかに効率良く高精度な翻訳規則を獲得するかが解決すべき重要な問題となっている．本論文ではこの問題を解決するため，翻訳例文から機械翻訳用の規則を抽出する方法を提案する．この手法ではまず，対訳例文の形態素解析を行い，対訳単語の対(ペア)を同定する．そして，同定できた単語ペアの品詞分類により，単語ペアの推定を行う．また，同定できない単語について，人間の援助により，すべての単語ペアを推定する．このような情報を用いて，システムでは自動的に翻訳規則を獲得する．この翻訳規則は構文構造レベルの対応関係を持ち，訳語の選択規則や複数単語から構成された文型パターンからなる． (Keyword) 機械翻訳システム / 対訳単語の対 / 翻訳規則
386.	Fuji Ren : Super-Function Based Machine Translation, Communications of COLIPS, Vol.9, No.1, 83-100, 1999. (Summary) 高精度の機械翻訳システムを実現するために，ここ数十年にわたって，構文解析，意味解析，さらには文脈情報を利用するといった方法による数多くの機械翻訳システムが実用化されてきた．このような従来の研究では，流暢な訳文の生成並びに翻訳作業の自動化もしくは半自動化を目的としてきたが，現段階では多くの問題が未解決のまま残されている．本論文では，インターネットの急速な普及という情報社会の現状を鑑み，流暢な訳文の生成より，外国語情報をすばやく母国語で拾い読みすることを機械翻訳の目的とする考えに基づき，構文解析や意味解析などは行わず，単に言語と言語との間の構造関係を用いる多国語機械翻訳方法を提案する．本論文では，言語間の対応関係パターンをスーパー関数と定義し，このようなスーパー関数を用い，翻訳を行う． (Keyword) スーパー関数 / 機械翻訳システム / 意味解析 / 構文解析
387.	Fuji Ren : The Concept of Sensitive Word in Chinese, --- Survey in a Machine-Readable Dictionary ---, Journal of Natural Language Processing, Vol.6, No.1, 59-78, 1999. (Summary) 言語理解についてまず自然言語文を正確に解析しなければならないが，中国語や日本語など連続的に書かれている文に対し形態素解析は極めて重要である．特に中国語文では日本語の格助詞がないので，形態素解析は非常に困難である．多くの言語には，特殊な性能をもつ語群がある．例えば，形態素解析を行う際に，一番困難なことは組み合わせ的な性質をもつ曖昧性をいかに解消するかである．しかしながら，従来の方法ではこの問題を解決できないと考えられる．本論文ではこの問題を解決するため，「敏感語」という新しい概念及び解決方法を提案した．我々は，多くの曖昧性をもつ文字列なかに，数の少ない敏感語のみ検討すればよいという規則を発見した．我々は80,000規模の電子化辞書を用い実験と考察を行い，本論文で提案した方法の有効性を確認することが出来た． [担当部分]方法論，アルゴリズムの開発，実験システムの構築，まとめを担当した． (Keyword) 自然言語文 / 敏感語 / 形態素解析 / 言語理解
388.	Fuji Ren and Fan Lixin : A New Approach to Using Corpus in Machine Translation, INFORMATION, Vol.1, No.2, 85-103, 1998. (Summary) 本論文では翻訳規則に基づく新しい機械翻訳アプローチを提案する．これらの翻訳規則はコーパスから抽出したものであるが，伝統的なコーパスに基づくアプローチとは異なり，規則獲得システムは機械翻訳システムから切り離す．即ち，我々がまずコーパスから翻訳規則を抽出し，それを開発者に確認させてから，これらの規則を機械翻訳システムに組み込んでいる．このアプローチは実例による翻訳手法の利点を継承できると同時に，処理時間と記憶のコストをあまり増やさない．したがって，このアプローチは，速い反応と高い精度を必要条件とする実際的な機械翻訳システムの構築に応用可能であると考えられる．我々は本論文で提案する手法に基づく日中機械翻訳システムを構築し，いろいろな実験を行った． (Keyword) 翻訳規則 / 機械翻訳
389.	Zhang Jianping, Fuji Ren and Ren Deguan : Algorithm Study on Large-Scale Feature Selection Problem, Journal of Tsinghua University, Vol.38, No.s2, 154-156, 1998. (Summary) 大規模特徴抽出問題は人工知能研究において極めて重要な問題の一つである．従来，大規模特徴を抽出するために，いろいろな手法が提案されたが，多くの問題が残されている．このような従来の手法をシステム的に纏め，今後の研究方向を把握することが当面解決しなければならない課題である．本論文では人工知能における知識獲得及び特徴抽出に研究し，大規模特徴抽出問題の新しいアルゴリズムを提案した．このアルゴリズムに基づく実験システムを開発し，いろいろなシミュレーションを行った． (Keyword) 大規模特徴抽出問題 / 人工知能 / 知識獲得
390.	Fuji Ren and Luo Zhensheng : A Multilayer Integration Approach to the Automatic Checking and Correction of Texts, Technical Report, HCU, Vol.98, No.5, 1-11, 1998. (Summary) Special features of Chinese characters and texts present considerable challenges for the automatic checking and correction of Chinese texts. We present a multilayer integration approach that which combines the rule-based method and the probability-based method to the automatic checking and correction of Chinese texts. First common error types in Chinese texts are analyzed. Then our research system employing the integration approach is discussed in detail.
391.	Fuji Ren, Jian Youliang and Nie Jianyun : Automatic Acquisition of Japanese-Chinese Translation Knowledge from Parallel Corpora, Technical Report, HCU, Vol.98, No.4, 1-16, 1998. (Summary) A crucial problem in rule-based machine translation is the acquisition of translation knowledge. In this paper, we describe a semi automatic process which acquires translation knowledge from examples in Japanese-Chinese translation. The acquired knowledge may concern syntactic structures of sentences in both languages and their correspondence, the constraints associated with the sentence structures, the dependence relationships between words, and so on. Once the acquired knowledge is integrated with an MT system, we observe an improvement in translation quality for the phenomena covered by the examples.
392.	Fuji Ren, Jane Youliang, Chang Hongtao and Ma ZhengYang : Automatic Acquisition of Machine Translation Rule from Parallel Corpora, Communications of COLIPS, Vol.8, No.1, 43-69, 1998. (Summary) Many Machine Translation (MT) systems use rules to transfer a sentence from the source language to the target language. It is a pre-requisite that the rules used have a good coverage of the linguistic phenomena of the domain of interest. How to acquire the necessary translation rules is a crucial problem. In this paper, A new approach of automatic acquisition of Machine Translation Rule from Parallel Corpora is presented. In the approach, we assume the presence of a "user" who may provide the system with additional information. A user is a person who has linguistic knowledge on both source and target languages. He will be asked to indicate the focus word of an example, to annotate the corresponding components in both sentences, and to choose the appropriate level of generalization for the example. The user works in interaction with the system. In this way, one does not need to annotate all the information uniformly for all the examples. If the system is able to produce a translation rule with the knowledge already acquired, the user is only asked to confirm it. Unnecessary manual annotation may be saved. Our preliminary experiments show that with the new knowledge, the quality of translation is greatly improved, and the extraction of rules prove to be much more efficient than the manual process. (Keyword) Machine Translation systems / Translation Rule / Automatic Acquisition
393.	Fuji Ren and Nie Jianyun : Concept of Sensitive Word, Technical Report, HCU, Vol.97, No.8, 1-11, 1997. (Summary) In Machine Translation (MT), using compound words or phases makes the translation process easier. For example, the phrase ``information highway''. It is not necessary to break it down to ``information'' and ``highway''. However, some compound words(phrases) in Chinese are composed of simpler words which can play significantly different roles in sentences when they are broken down. For example, the compound word ``machine translation'' may be broken into ``machine'' and ``translate'', as in the sentence ``He uses a machine to translate papers''. We call such a compound word a sensitive. During Chinese MT processing, if the first segmentation result leads to a failure, the alterative solution with a sensitive word broken down is considered as the preferred one. This allows us to reach at a higher efficiency by avoiding examining impossible segmentation solutions. In this paper, we describe the problems related to sensitive words. A machine readable dictionary has been examined, and more than 800 sensitive words have been found. This shows that sensitive word is a common phenomenon in Chinese that is worth closer examination.
394.	Fuji Ren and Ma Hongming : A Robust Machine Translation System Based on Multi-Processes, Communications of COLIPS, Vol.7, No.1, 17-26, 1997. (Summary) 母親は赤ちゃんのなき声を聞いて，赤ちゃんは母親に何かを訴えることを理解できる．恋人の間，夫婦間の発話では，語がいくつか並べられるだけで，コミュニケーションができ，互いに理解できる．これはなぜでだろうか?我々は人間のコミュニケーションメカニズムの解明をしているが，これはいろいろな制約，いろいろな世界知識の作用によるものと考えられる．コンピュータによる言語理解とコミュニケーシュンではいかに人間のコミュニケーシュンにおけるルバストをコンピュータで実現するかが非常に重要な課題である．本論文では複数のプロセスを利用しそれぞれの言語現象にその特徴を利用し頑健性を持たせる自然言語処理システムを構築する方法論を提案した．さらに，この方法に基づいてプロトタイプシステムを開発し実験と考察を行った． (Keyword) communication / 世界知識 / 言語現象 / 頑健性 / 機械翻訳
395.	Fuji Ren : An Algorithm for Determining Structural Particle, Technical Report, HCU, Vol.97, No.5, 1997. (Summary) In a machine translation system from one language to Chinese, it is difficult to decide whether there is a structural particle ``DE'' between the ``DingYu'' and the ``ZhongXinCi'' where DingYu is a term in Chinese grammar. It resembles the modifier and the limitation word in Japanese, but not the same. The ZhongXinCi is referred to the word modified by DingYu. In this paper, we present a new method for deciding the existence of the structural particle ``DE'' and show an experiment result of the method. A particle Japanese-Chinese machine translation system based translation rules has been implemented by authors, this systems lacks the ability for resolving the problem mentioned above. To resolve this problem, we firstly collect lots of grammar items from Chinese grammar books, and get some elementary judgment rule by classifying and inducing these grammar items, and then we put these judgment rules into use in actual Chinese language, and modify the rules by checking its results instantly. The last we check and modify the rules by using a actual corpus. A experimental system based on these rules has been constructed and an experiment is carried out. The result shows the effectiveness of the proposed method.
396.	Fuji Ren : Super-Function Based Machine Translation Approach, Technical Report, HCU, Vol.97, No.3, 1-16, 1997. (Summary) Over the last decade, the number and diversity of experiments in Rule-Based Machine Translation, Knowledge-Based Machine Translation, and Example-Based Machine Translation have grown significantly. Most of these methods are aiming to build an Automatic High-Quality Translation System (AHQTS). In this paper, we present a new Machine Translation approach called Super-Function Based MT. We use a Super-Function (SF) in the translation engine to enhance the translation quality and to reduce the glossary quality. The Super-Function is a function that shows the correspondence between original language sentence patterns and target language sentence patterns. We used TTB to store SF and to match SF with the input sentence. An experiment on the Japanese-English-Chinese textbook has been simulated. The 61 SFs are acquired and the result shows that this method is efficient.
397.	Fuji Ren : Machine Translation and Empirical Knowledge, Science and Technology, Vol.2, No.2, 35-55, 1996. (Summary) 多言語処理技術が21世紀の3大情報インフラの一つとして位置つけられる．その中に，機械翻訳は言語処理における中心的な課題である．本論文では機械翻訳の歴史と現状を分析し，人間に有用な機械翻訳システムを構築するための技術を述べて，21世紀における機械翻訳の研究課題と発展動態を展望する．80年代は，機械翻訳をはじめとして，自然言語処理·自然言語理解システムへの期待が高まったが，90年代に入っていささか沈静化したように見える．本稿では，機械翻訳研究開発が間もなく再び隆盛を迎えると主張する．また，本稿では，経験知識を機械翻訳に導入するアプローチを提案し，特にいかにコーパスや実際な人間コミュニケーシュン場面からいろいろな経験知識を抽出するかの試みをした考察を述べる． (Keyword) 言語処理技術 / 経験知識 / 機械翻訳
398.	Fuji Ren : Cooperative Distributed Processing for Machine Translation, Technical Report, HCU, Vol.96, No.6, 1-8, 1996. (Summary) In natural dialogues, speakers make many kinds of ill-formed sentences such as ellipsis. A robust natural language processing system must be able to allow such ill-formed sentences and derive correct interpretations from the ill-formed sentences. But existing machine translation systems reject utterances including ellipses and ill-formed expressions. In this paper, a new concept, Persisting Ellipsis and Critical Ellipsis in machine translation, is put forward, and a method for handling ill-formed sentences, called Cooperative Distributed Machine Translation (CDMT), is presented. The CDMT advocates the ideas: (1) All Constraint based translation process, (2) Syntactic-Constraint based translation process, and (3) Semantic-Constraint based translation process. An experimental system based on this method has been constructed and some results are given in this paper. The results show that CDMT is a promising technique for high-quality and efficient spoken language machine translation.
399.	Fuji Ren : 複数のプロセスを用いた協調融合型機械翻訳, HCU-IS, Vol.96, No.5, 1-21, 1996. (Summary) In natural dialogues, speakers make many kinds of ill-formed sentences such as ellipsis. A robust natural language processing system must be able to allow such ill-formed sentences and derive correct interpretations from the ill-formed sentences. But existing machine translation systems reject utterances including ellipses and ill-formed expressions. In this paper, a new concept, Persisting Ellipsis and Critical Ellipsis in machine translation, is put forward, and a method for handling ill-formed sentences, called Cooperative Distributed Machine Translation (CDMT), is presented. The CDMT advocates the ideas: (1) All Constraint based translation process, (2) Syntactic-Constraint based translation process, and (3) Semantic-Constraint based translation process. An experimental system based on this method has been constructed and some results are given in this paper. The results show that CDMT is a promising technique for high-quality and efficient spoken language machine translation.
400.	Fuji Ren : SWKJC Machine Translation System Based on Translation Rules Acquired from Corpora, Technical Report, HCU, Vol.96, No.4, 1-31, 1996. (Summary) This paper proposes a method of machine translation system based on translation rules which extract from very large corpora. Unlike in traditional approaches, corpora are separated from translation system. This means that we acquire translation rules from corpora first, and then construct translation system using these translation rules. Therefore, this method fulfills the quick response and high accuracy requirements of a practical machine translation system. The translation rules in this paper refer to word selection rules and translation templates that represent word-level, phrase-level and idiomatic expression-level translation rules.
401.	Fuji Ren : 次世代自然言語における超並列処理について, HCU-IS, Vol.95, No.23, 1-19, 1995. (Summary) 現在のVLSI技術の進歩には著しいものがあり，従来では不可能であったような計算パワー，メモリ空間が容易に得られるようになってきた．さらに，VLSIの実装密度が飛躍的に向上し数万オーダのプロセッサを実装するような状況下で現実性を帯びてきた計算機アーキテクチャが超並列マシンであり，既にいくつかの製品が発表，販売されている．このような計算機アーキテクチャの革新は，自然言語処理にも影響を与えることは明らかである．このような背景で超並列自然言語処理が必ず登場していると考えられる．また，実現している超並列ハードウエアの特徴と自然言語処理の超並列性が必ずしも一致していない現実もあり，認知理論や言語理論における超並列の必要性の明確化ならびに処理手法レベルでの超並列処理の特徴を考察することは重要なことである．本論文ではまず超並列計算機の出現背景及びハードウエア技術などを考察する．特に，超並列機械翻訳という新しいパラダイムを提案し，いくつかの並列手法を述べる．さらに，現在のモデルで超並列自然言語処理をするときの問題点を考察する．最後に超並列自然言語処理今後の課題について述べる．
402.	Fuji Ren : Processing Method of Reservable Structural Ambiguities in Machine Translation, Technical Report, HCU, Vol.95, No.18, 1-18, 1995. (Summary) In this paper, a new concept, Reservable Structural Ambiguities (RSA) in Japanese-Chinese machine translation, is put forward. The RSA is structural ambiguities of Japanese that can be translated into Chinese without being resolved. Usually, when translating one language to another which doesn't belong to the same ``language family'', structural ambiguities must be resolved. Japanese and Chinese do not belong to the same family and their difference is mainly on sentence structure. However, some parts of their sentences are similar which makes RSA possible. This paper focuses on above issues. Some RSA patterns are discussed and a method for the generation of Chinese from Japanese sentences with RSA is described. (Keyword) 多言語処理技術 / 機械翻訳システム / 経験知識 / 人間コミュニケーシュン
403.	Fuji Ren : Natural Language Processing, Science and Technology, Vol.1, No.1, 51-62, 1995. (Summary) 本稿では，記号処理人工知能の典型である自然言語処理の今後の動向について述べる．次世代自然言語処理では世界知識をいかに有効的に利用するかが重要な課題である．本論文ではまず自然言語処理の基本的な流れを述べ，その直面する問題を考察し分類を行う．そして，言語理解という視点から自然言語の曖昧性及び人間のコミュニケーシュンでその曖昧性の対処メカニズムを検討し，オントロジーの自動構築手法を提案する．本稿では，次の幾つかの面で興味深く議論を行う．まず，現在の自然言語処理の研究課題として，曖昧性および曖昧性の解消，頑健性自然言語処理，超並列自然言語処理，言語の生成，解析と生成の融合について述べる．そして，知的対話処理，音声と言語との融合，機械翻訳，大規模コーパスについて述べ，日本での研究現状を考察する． (Keyword) 自然言語処理 / 曖昧性 / コミュニケーシュン / 超並列自然言語処理 / 知的対話処理
404.	范莉馨, Fuji Ren, 宮永喜一 and 栃内香次 : 関連語を用いた文の分解に基づく中日機械翻訳システム, Transactions of Information Processing Society of Japan, Vol.35, No.12, 2712-2724, 1994. (Summary) 自然言語処理，例えば機械翻訳において，複文の処理は極めて重要であり，それも大変困難である．中国語文の実際上の使用度から見ると，単文が極めて少なく，複文の方が多い．従って，中国語機械翻訳システムの実用という見地から言えば，複文の翻訳は極めて重要である．本論文では，中国語複文と日本語複文との対応関係を検討し，関連語を用いて複文をいくつかの単文に分解し，それぞれの単文の翻訳結果から最終の訳文を生成する手法を提案した．また，関連語の処理を効率的に行うために，多数の教科書及び科学技術文献から関連語に対応する訳文の文型を抽出してそれらを訳文関数と名付け，入力された中国語文中で関連語が認識されたなら，詳細な文法解析を行わず，訳文関数を用いて直接訳文を生成している．さらに，関連語の多義性を解消するため，関連語に関係する要素の意味属性を用いて多義性の解消を行っている． (Keyword) 中国語複文 / 日本語複文 / 中国語機械翻訳システム / 関連語
405.	范莉馨, Fuji Ren, 宮永喜一 and 栃内香次 : 中日機械翻訳における離合詞の処理手法, Transactions of Information Processing Society of Japan, Vol.35, No.9, 1702-1713, 1994. (Summary) 言語には，系統または規則的な面と無系統または無規則的な面の両面があり，さらには離散的，連続的という両面もあると考えられる．その一例として，我々の研究開発している中日機械翻訳において，中国語の「詞」，特に「離合詞」を考える．離合詞とは，一つの単語は別の単語によっていくつかの部分に分離されているものである．このような離合詞を上手く認識できなければ，機械翻訳はもちろん，形態素解析，構文解析も正確に行われないと考える．本論文ではこのような離合詞の認識方法を提案し，さらにそれを中日機械翻訳へ応用する方式を述べた． (Keyword) 離合詞 / 機械翻訳 / 規則
406.	Fuji Ren, 范莉馨, 宮永喜一 and 栃内香次 : 日中機械翻訳における係り受け構造の可保留曖昧関係について, Transactions of Information Processing Society of Japan, Vol.34, No.8, 1682-1691, 1993. (Summary) 非同族言語間の機械翻訳では，原言語の係り受け構造の曖昧性をあらかじめ解消しなければならないと言われている．日本語と中国語は非同族の言語であり，文全体の構造は異なるが，文のある部分ではその語順が同じ部分が存在する．この同じ部分に関しては，日本語の係り受け構造の曖昧性を残したまま翻訳された中国語においても日本語の意味を支障なく復元されると考えられる．この部分の翻訳は，あらかじめ与えておいた訳文関数を用いて行うことができる．本論文では，上記のことに着目して日中機械翻訳における可保留曖昧関係を提案する．可保留曖昧関係は原言語の係り受け構造の曖昧性を解消しなくてもその訳文を生成できる曖昧関係である．具体例として，並列助詞「と」と連体助詞「の」と名詞からなる名詞句および用言連体形からなる文の係り受け構造の可保留曖昧関係について検討し，翻訳手法を提案した．可保留曖昧関係という概念は他の言語ペアに対しても有効であると考える． (Keyword) 非同族言語 / 係り受け構造 / 曖昧性 / 可保留曖昧関係 / 翻訳手法
407.	Fuji Ren : On Reservable Structural Ambiguities in JCMT, Journal of Dalian University of Technology, Vol.33, No.2, 242-251, 1993. (Summary) A new concept, Reservable Structural Ambiguities (RSA) in Japanese-Chinese machine translation, is presented. The RSA are structural ambiguities of Japanese which can be translated into Chinese without being resolved. Usually, when translating one language into the other which doesn't belong to the same ``language family'', structural ambiguities must be resolved. However, Japanese and Chinese don't belong to the same family, their differences being mostly on sentence structure. However, some parts of their sentences are similar, making RSA possible, and this paper will focus on them. Some RSA patterns will be discussed and a method for generation of Chinese from Japanese sentences with RSA will be given. An experimental system based on this method has been constructed and an experiment has been carried. The result is correct translation rate of about 97.6 %, showing that the proposed method is quite effective. (Keyword) Reservable Structural Ambiguities / Japanese-Chinese machine translation
408.	范莉馨, Fuji Ren, 栃内香次 and 宮永喜一 : 中日機械翻訳における複合語の自動合成, Transactions of Information Processing Society of Japan, Vol.33, No.9, 1103-1113, 1992. (Summary) 機械翻訳において，出来るだけ長い単語を認識して翻訳ルールを適当するのが望ましい．本論文では，中国語の複合語の特徴を検討し，複合語の自動合成手法を提案した．さらに，複合語の日中機械翻訳方法を開発し，実験システムに組み込んでいろいろな翻訳実験を行った結果，本論文で提案した手法は中日機械翻訳システムに極めて有効であることを確認した． (Keyword) 複合語 / 機械翻訳
409.	Fuji Ren, 宮永喜一 and 栃内香次 : 意味属性による補助語の推定アルゴリズム, Transactions of Information Processing Society of Japan, Vol.32, No.11, 1374-1382, 1991. (Summary) 日中機械翻訳システムを研究するためには，(1)独立品詞の語順の確定，(2)補助語とくに日本語格助詞に対応する補助語の推定が必要と考えられる．本論文では(2)について論じる．一般に，日本語の各助詞に対応する中国語補助語は一対多であるので，複数補助語候補から正しい補助語の推定は日中機械翻訳を行うとき解決しなければならないという問題がある．本論文では，まず，教科書，文献など約12000文から格助詞及びその関連情報を抽出し，この情報を分析してから，意味属性による日本語格助詞に対応する中国語補助語を推定する手法を提案する．そして，格助詞の多義性を解消する役割をもつ日本語格助詞と中国語補助語との関連表を求め，格助詞を含む1200文の実験を行った．その結果により，提案した手法の有効性を確認することが出来た． (Keyword) 補助語 / 意味属性 / 格助詞 / 日中機械翻訳システム
410.	Fuji Ren, 范莉馨, 宮永喜一 and 栃内香次 : 家族モデルを用いた文の分解に基づく日中機械翻訳システム, Transactions of Information Processing Society of Japan, Vol.32, No.10, 1249-1258, 1991. (Summary) 本論文では文の分解による家族モデルを提案し，このモデルを用いた日中機械翻訳実験システムを述べる．家族モデルは父親モジュール，太郎モジュール，次郎モジュール，花子モジュールからなる．父親モジュールは翻訳全体の制御，特に入力文を基本文と常用文型に分解する．太郎モジュールは，基本文の解析を行い，目的言語文法に従って語順の調整を行う．次郎モジュールは，常用文型の処理を行う．花子モジュールは補助語を推定する．最後に，父親モジュールによってすべての情報を総合して訳文を整理する．4つのモジュールが独立的に構築されるので，翻訳システムの改良などが容易に実現される．また，太郎，次郎，花子モジュールは相互間に情報交換がないので，並列処理ができる． (Keyword) 家族モデル / 日中機械翻訳
411.	Fuji Ren, 宮永喜一 and 栃内香次 : 日中常用文型機械翻訳システム, The Transactions of the Institute of Electronics, Information and Communication Engineers D-II, Vol.74, No.8, 1060-1069, 1991. (Summary) 日本語の文章に頻繁に現れる文型を常用文型と定義する．このような文型を人間が翻訳する場合，その部分の詳しい文法分析を行わず直接に訳文を得ている．本論文ではこのような人間の翻訳方法を見習い，コンピュータでの実現する手法を開発した．この手法で得られた中国語訳文は，常用文型に対応して選択された補助語によりアスペクトやモダリティを満足する．本手法の要点は，(1)各々の常用文型についてその訳文条件を調べ，訳文関数を求めること，(2)訳文関数を用いて直接訳文を生成すること，(3)意味属性によって多義性を解消すること，の3点にまとめられる．この手法は大別して次の3つの部分より構成される．(1)日本語文の解析ならびに常用文型の抽出，(2)日本語常用文型に対応する中国語表現の多義性と多訳性の解消，(3)中国語表現に現れる補助語の語順および修飾対象の確定． (Keyword) 常用文型 / 機械翻訳 / 中国語 / 日本語
412.	Fuji Ren : Fanout Point-Oriented Fault Simulation in VLSI, Journal of Chinese Computer, Vol.13, No.2, 133-138, 1990. (Summary) VLSIの故障検査を行う場合，回路を分割して試験したり，回路中の信号をモニタすることが困難であるために，大規模な回路では故障試験に膨大な入力系列(検査系列)を必要とする．しかし，このような検出できる故障をシミュレーションすると，やはり膨大な時間が必要であるので，その高速化が求められている．本論文では，分岐点指向の並列大規模な論理システムの故障シミュレーション方法を提案した．従来の手法では，すべての節点をシミュレーションしなければならないが，本方法では分岐点のみを行う．また，本手法では，正常回路と複数の故障回路の論理値をホスト計算機の1ワードのビット演算を用いてシミュレーションを行う．それで，ビット演算の並列処理による高速化が達成されている．統計によると，平均的に分岐点は5分の1から10分の1程度で，本手法は極めて高速である．そして，理論的にこの手法の正確性を証明できた． (Keyword) Fault Simulation / VLSI
413.	Fuji Ren and Wei Daozheng : Fault Simulation Algorithm for Multiple-Valued Logic Systems, Journal of Microelectric Test, Vol.2, No.4, 36-41, 1988. (Summary) 多値論理回路の故障シミュレーションは2値論理回路と異なり，従来の手法では膨大な探索時間が必要なので，大規模な回路について流用できない．本論文では多値論理回路の故障診断の新しい手法を提案した．この手法では，分岐点のみに並列な手法で故障シミュレーションを行い，他の節店に簡単な探索で故障点を同定できるので，高い効率ですべての故障を検索するこつができる．分岐点とは，該節点から一つ以上の経路が存在し，なおかつ，全体的に回路を形成している節点である．本論文では，このような分岐点だけ故障の伝播に敏感であり，このような点の故障を同定できれば，多の節点の故障を簡単に検索できることを示した．幾つかの回路を用い，実験を行ったが，本手法の有効性を確認するこつができた． (Keyword) Multiple-Valued Logic System / Fault Simulation
414.	Chen Junliang, Fuji Ren and Ma Yue : Graph Algorithm for Fault Simulation in Digital System, Journal of Beijing University of Posts and Telecommunications, Vol.10, No.3, 1-10, 1987. (Summary) A new graph algorithm for fault simulation in digital systems is presented. The basic idea of the graph algorithm is to make use of the structural information of the digital system to replace operations on fault lists as used in conventional fault simulation algorithms. The first step in the graph algorithm is to transform a digital system into a special kind of graph named conditional digraph. All sensitized paths (called 1 paths) are identified by traversing the conditional digraph using graph theoretical methods. All faults on 1 paths reachable to the primary outputs of the digital system can be detected. The algorithm for fault simulation in synchronous sequential circuits is given. Graph models for digital systems with memory chips and methods for memory space compression are also described in this paper. (Keyword) fault simulation / digital system / Graph Algorithm
415.	Fuji Ren : An Algorithm for Determining Chromatic Number and the Practical Approach, Journal of Computer Applications and Software, Vol.3, No.4, 58-63, 1986. (Summary) To determine Chromatic Number in graph theory is a very difficult problem. In this paper, an algorithm for determining Chromatic Number, called Matrix-Compatible-Covering, is presented. A practical approach based on this algorithm is also given. The algorithm can be used to solve the storage problem, school timetable problem etc. This algorithm is easy to understand as well as to be implemented in computers. An experimental system based on the algorithm has been constructed and an experiment on university timetable has been carried. The result shows that the proposed method is quite effective. (Keyword) Chromatic Number / school timetable problem

Academic Paper (Unrefereed Paper):

1.	大坂京子, Shin-ichi Chiba, Tetsuya Tanioka, Yuko Yasuhara, Fuji Ren, Chiemi Kawanishi, 高坂要一郎, 三船和史 and 大森美津子 : Uses of the Electronic Nursing Management System, PSYCHOMS® , in Psychiatric Hospitals : Process, Current State, and Future Development, Nursing Journal of Kagawa University, Vol.16, No.1, 85-91, 2012. (Summary) The purpose of this article is to introduce the development process, mechanism, and functions of the PSYCHOMS® (Psychiatric Outcome Management System). Also, it reports on agenda for commercialization of research achievement of the PSYCHOMS®(regis-tered trademark, Takasaka et al.). Our team has been developing the PSYCHOMS® since 2006. This system has four major components: (1) clinical pathway and variance analyzing system, (2) nursing manager and staff's daily recording system, (3) nursing care planning system, and (4) nursing management support system. Also, any interdisciplinary team member can access the patient's information using this system. Therefore, each interdisciplinary team member's expertise can be utilized maximally for the patient's benefit and for improved total outcomes. It was then necessary to conduct a survey on what standard items were common in these hospitals for data base of the PSYCHOMS®. As future research problem using PSYCHOMS®, in order to improve psychiatry service, it is necessary to develop the database common to each psychiatric hospital. (Keyword) 精神科看護管理システム / クリニカルパス / 看護管理日誌 / 看護診断 / アウトカム (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1520853833870344960 (CiNii: 1520853833870344960)
2.	片岡睦子, Tetsuya Tanioka, Hiroki Moriguchi, Isao Nagamine, 高坂要一郎, Fuji Ren, 山本亜衣, 西村美香, 岸本真由子, 中屋公子, Toshiko Tada, Fumiko Hashimoto, Yasuko Matsushita, Ruriko Yamashita and 後藤新市 : 急性期治療病棟で用いる統合失調症用のクリニカルパスをベースとしたアウトカム管理者の職務内容の検討, 季刊こころの臨床 a·la·care, Vol.24, No.2, 229-244, 2005. (Summary) 近年，ケアの質改善を目指してクリニカルパスは用いられるようになった．しかし日本では，統合失調症患者のためのクリニカルパスとアウトカム管理のための項目は十分に検討されていない．この研究の目的は，急性期治療病棟で用いる統合失調症用のクリニカルパスをベースとしたアウトカム管理の確認項目の検討を通してアウトカム管理を担うものの職務内容を明確化することである．筆者らは，(Interdisciplinary Collaborative Team Care Model: ICTCM)を2000年に導入し，1999年の平均在院日数205．7日(1994年の平均在院日数675．5日)を2004年には155．2日に短縮した精神科専門の病院(ベッド数243床，病床回転率235．9%，病床利用率86．8%)において，学際的なケア提供者と事務責任者を調査対象として，聞き取り調査を行った．その結果から，急性期治療病棟で用いる統合失調症用のクリニカルパスをベースとしたアウトカム管理を行うための職務内容の詳細を明確にした． (Keyword) schizophrenia / Outcome Management / Clinical Path / Nursing Administration / Team Care (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1571698600792579840 (CiNii: 1571698600792579840)
3.	Shin-ichi Chiba, Fuji Ren, Shingo Kuroiwa and Tetsuya Tanioka : Analysis of electroencephalographic activity in condition of emotional activation in human, International Conference on Artificial Intelligence and Soft Computing, Vol.1, No.1, 445-450, 2005.

Review, Commentary:

1.	Fuji Ren and Yu Gu : Motion and Emotion Sensing Driven by Big Data, ZTE Communications, Vol.15, No.S2, 1-2, Dec. 2017. (Summary) Inthispaper,wedescribeamethodofemotionanalysisonsocialbigdata.SocialbigdatameanstextdatathatisemergingonIn ternetsocialnetworkingservices.Wecollectmultilingualwebcorporaandannotatedemotiontagstothesecorporaforthepurpose ofemotionanalysis.Becausethesedataareconstructedbymanualannotation,theirqualityishighbuttheirquantityislow.Ifwe createanemotionanalysismodelbasedonthiscorpuswithhighqualityandusethemodelfortheanalysisofsocialbigdata,we mightbeabletostatisticallyanalyzeemotionalsensesandbehaviorofthepeopleinInternetcommunications,whichwecouldnot knowbefore.Inthispaper,wecreateanemotionanalysismodelthatintegratethehigh qualityemotioncorpusandtheautomatic constructedcorpusthatwecreatedinourpaststudies,andthenanalyzealarge scalecorpusconsistingofTwittertweetsbasedon themodel.Astheresultoftime seriesanalysisonthelarge scalecorpusandtheresultofmodelevaluation,weshowtheeffective nessofourproposedmethod.
2.	Zhong Huang, Fuji Ren and Min Hu : Present situation and development of intelligent robots, ROBOT, Vol.38, No.2, 225-232, Feb. 2016. (Summary) To overcome the limitations in manually setting the control parameters of facial expressions with motors of limited number, an online facial expression imitation algorithm is proposed for humanoid robot based on RBF (radial basis function) neural network by combining the Kinect based AAM (active appearance model). In the offline facial expression learning phase, a forward mechanic model is modeled based on RBF networks to reflect the mapping relationship between the motor control values and the facial deformation characteristics, and an inverse prediction model is further developed for wrapping the smoothness of continuous motor movements. In the online facial expression imitating phase, optimal motor values are solved to minimize deformation deviations between the robot and the performer, based on the forward mechanic model and the inverse prediction model; moreover, a weighting factor is introduced to adjust the instantaneous similarity of expression imitation and the smoothness of motor's continuous motion. Finally, the rationality and generalization ability of the two models are validated from the perspective of mean statistics and prediction deviations, and the influence of weighting factor on space-time similarity and smoothness is further discussed. The experimental results indicate that the deformation deviations of the forward mechanic model are less than 1%, and the motor control deviations of the inverse prediction model are less than 1.5%. Compared with the three methods of Jaeckel, Trovato and Magtanong, the proposed algorithm has advantages in the similarity of single-frame expression imitation and the smoothness of multi-frame expression motion. (Keyword) humanoid robot / RBF (radial basis function) neural network / online facial expression imitation / facial expression similarity / motion smoothness (Link to Publication Site) ● Publication site (DOI): 10.13973/j.cnki.robot.2016.0225 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.13973/j.cnki.robot.2016.0225 (DOI: 10.13973/j.cnki.robot.2016.0225)
3.	Fuji Ren and Xiao Sun : Present situation and development of intelligent robots, Science & Technology Review, Vol.33, No.21, 32-38, Nov. 2015. (Summary) With the development of scientific and technological progress and social development, people want to be more free from tedious daily affairs. This promotes the development of intelligent robot market. In addition, Intelligent robot industry is deemed as a measure of a national science and technology innovation status and an important symbol of the level of high-end manufacturing, its development has received more and more attention around the world. This article describes the current situation and the development level of domestic and international communities of intelligent robots, including intelligent robot technology and classification of robots, applications of intelligent robot in all walks, and has explored the intelligent robots' development trends and outlook. (Keyword) intelligent robot / artificial intelligence / development status / prospects / forecast
4.	Yu Wang, Fuji Ren and Changqin Quan : Review of Dialogue Management Methods in Spoken Dialogue System, Computer Science, Vol.42, No.6, 1-8, Jun. 2015. (Summary) 音声会話システムは人工知能における重要な分野であり，近年，快速に研究開発されている．本稿では，音声システムの概要，現状，課題，そして今後の展望について考察し，特に，これから音声会話に関する研究方向と応用について述べる．さらに，音声会話システムのモジュール構築，モジュール間の管理，モジュール機能拡張に調査と分析を行った．
5.	Fuji Ren : Robotic Cloud and Robotic School, Science and Technology Review, Vol.30, No.9, 73-79, Mar. 2012. (Summary) In the near future, robots with advanced intelligence will be used for the service of society, families, and individuals. The concept of an advanced intelligence machine, which is a device that uses both natural and artificial intelligence and is capable of affective recognition and generation of affective speech and behavior, is proposed in this paper. We describe the concept of a ``robotics cloud'' for use by advanced intelligence machines in human robot interactions and provide a theoretical framework and technology blueprint of the construction of a robotics cloud. In addition, we propose a ``robotics school'' for building robotics clouds and describe a framework for the school, its certification program, and a method for authentication of the school. The influence of robots on the development of society, scientific and technological progress, and human robot relationships are also discussed. (Keyword) advanced intelligence machine / robotics cloud / robotics school / robotics certification and robotics degrees / human robot interaction / human-machine robot
6.	光吉俊二 and Fuji Ren : Emotion Recognition, The Journal of The Institute of Electrical Engineers of Japan, Vol.125, No.10, 641-644, Oct. 2005. (Summary) 機械が人間を理解するからには，機械が人間の心(感情状態)を感受できないといけない．そこには，「人間の感情は本人が自覚するより明確さに欠けている」という問題がある．感受性の基準となるべき人間の感情認識や，また「感情」として表層化される以前の心的特性の解明までには至っていない．本稿では人間の感情を測定する手法，問題点および今後の課題を解説する． (Keyword) 感情認識 / 主観評価比較 / 自然感情 / 意図的な感情 (Link to Publication Site) ● Publication site (DOI): 10.1541/ieejjournal.125.641 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1390001204662439552 ● Search Scopus @ Elsevier (DOI): 10.1541/ieejjournal.125.641 (DOI: 10.1541/ieejjournal.125.641, CiNii: 1390001204662439552)
7.	Fuji Ren and Shingo Kuroiwa : Multi-Lingual Multi-Function Multi-Media Intelligent System, Bulletin of Faculty of Engineering, The University of Tokushima, No.47, 21-34, Mar. 2002.

Proceeding of International Conference:

1.	Wang Linhuang, XIN KANG, Ding Fei, Haitao Yu, Yunong Wu, Kazuyuki Matsumoto, Nakagawa Satoshi and Fuji Ren : Self Decoupling-Reconstruction Network for Facial Expression Recognition, International Joint Conference on Neural Networks (IJCNN 2024), 1-8, Yokohama, Jul. 2024.
2.	Linhuang Wang, XIN KANG, Satoshi Nakagawa and Fuji Ren : Msstnet: A Multi-Scale Spatio-Temporal CNN-Transformer Network for Dynamic Facial Expression Recognition, The 49th IEEE International Conference on Acoustics, Speech, & Signal Processing (ICASSP 2024), 1-5, Apr. 2024. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICASSP48485.2024.10446699 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85201179213 (DOI: 10.1109/ICASSP48485.2024.10446699, Elsevier: Scopus)
3.	Yuxiang Zhou, XIN KANG, Fuji Ren, Satoshi Nakagawa and Xiao Shan : DEU-Net: Dual Encoder U-Net for 3D Medical Image Segmentation, The 22nd International Conference on Computer and Information Technology, 1-7, Nov. 2023. (Link to Publication Site) ● Publication site (DOI): 10.1109/TrustCom60117.2023.00382 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85195458711 (DOI: 10.1109/TrustCom60117.2023.00382, Elsevier: Scopus)
4.	Linhuang Wang, XIN KANG, Satoshi Nakagawa and Fuji Ren : CenterMatch: A Center Matching Method for Semi-supervised Facial Expression Recognition, The 6th Chinese Conference on Pattern Recognition and Computer Vision (PRCV 2023), 1-12, Oct. 2023. (Link to Publication Site) ● Publication site (DOI): 10.1007/978-981-99-8537-1_30 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85181773525 (DOI: 10.1007/978-981-99-8537-1_30, Elsevier: Scopus)
5.	Li Xiudong, XIN KANG and Fuji Ren : Use Active Learning to Construct Japanese Emoji Emotion Database, Communications in Computer and Information Science, Vol.1701, 332-340, Dec. 2022. (Link to Publication Site) ● Publication site (DOI): 10.1007/978-981-19-7943-9_29 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85145262078 (DOI: 10.1007/978-981-19-7943-9_29, Elsevier: Scopus)
6.	He Jiaxin, XIN KANG and Fuji Ren : Gait Recognition for Laboratory Safety Management Based on Human Body Pose Model, Communications in Computer and Information Science, Vol.1701, 323-331, Dec. 2022. (Link to Publication Site) ● Publication site (DOI): 10.1007/978-981-19-7943-9_28 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85145261599 (DOI: 10.1007/978-981-19-7943-9_28, Elsevier: Scopus)
7.	Haoyu Wang, XIN KANG and Fuji Ren : Emotion-Sentence-DistilBERT: A Sentence-BERT-Based Distillation Model for Text Emotion Classification, Communications in Computer and Information Science, Vol.1701, 313-322, Dec. 2022. (Link to Publication Site) ● Publication site (DOI): 10.1007/978-981-19-7943-9_27 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85145253184 (DOI: 10.1007/978-981-19-7943-9_27, Elsevier: Scopus)
8.	Zhou yuxiang, XIN KANG and Fuji Ren : MDSU-Net: A Multi-attention and Depthwise Separable Convolution Network for Stroke Lesion Segmentation, 2022 9th International Conference on Biomedical and Bioinformatics Engineering (ICBBE 2022), 1-14, Nov. 2022. (Link to Publication Site) ● Publication site (DOI): 10.1145/3574198.3574200 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85150363787 (DOI: 10.1145/3574198.3574200, Elsevier: Scopus)
9.	Fuji Ren, Jiao Ziyun and XIN KANG : Improved Transformer-based Implicit Latent GAN with Multi-headed Self-attention for Unconditional Text Generation, The Fifth International Conference on Intelligence Science (ICIS2022), Vol.659, 166-173, Oct. 2022. (Link to Publication Site) ● Publication site (DOI): 10.1007/978-3-031-14903-0_18 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85144543119 (DOI: 10.1007/978-3-031-14903-0_18, Elsevier: Scopus)
10.	Li Bin, Fuji Ren, Ni Hongjun, XIN KANG, Lv Shuaishuai and Hao Zhuangzhuang : Classification Method of Surface Defects of Aluminum Profile Based on Transfer Learning, International Conference on Machine Learning and Intelligent Systems Engineering (MLISE 2022), 1-5, Aug. 2022. (Link to Publication Site) ● Publication site (DOI): 10.1109/MLISE57402.2022.00008 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85143074519 (DOI: 10.1109/MLISE57402.2022.00008, Elsevier: Scopus)
11.	Ding Fei, XIN KANG, Yunong Wu and Fuji Ren : TUA1 at the NTCIR-16 DialEval-2 Task, Proceedings of the 16th NTCIR Conference on Evaluation of Information Access Technologies, 1-5, Jun. 2022.
12.	Zhou Yangyang, XIN KANG and Fuji Ren : Employing Contrastive Strategies for Multi-label Textual Emotion Recognition, 12th International Conference on Intelligent Information Processing (IIP2022), 13-24, May 2022. (Link to Publication Site) ● Publication site (DOI): 10.1007/978-3-031-03948-5_24 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85132047240 (DOI: 10.1007/978-3-031-03948-5_24, Elsevier: Scopus)
13.	Liu Zheng, XIN KANG and Fuji Ren : Improving speech emotion recognition by fusing pre-trained and acoustic features using Transformer and BiLSTM, 12th International Conference on Intelligent Information Processing (IIP2022), 1-12, May 2022. (Link to Publication Site) ● Publication site (DOI): 10.1007/978-3-031-03948-5_28 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85132037268 (DOI: 10.1007/978-3-031-03948-5_28, Elsevier: Scopus)
14.	Yuma Komoto, XIN KANG and Fuji Ren : Creating a Japanese dialogue corpus with multi-level topic analysis, 2022 4th International Conference on Natural Language Processing, Mar. 2022. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICNLP55136.2022.00065 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85139450830 (DOI: 10.1109/ICNLP55136.2022.00065, Elsevier: Scopus)
15.	Tatsuya Ikegami, XIN KANG and Fuji Ren : Improvement of Japanese Text Emotion Analysis by Active Learning Using Transformers Language Model, Proceeding of 2022 IEEE 14th International Conference on Computer Research and Development(ICCRD), 171-177, Jan. 2022. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICCRD54409.2022.9730387 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85127793016 (DOI: 10.1109/ICCRD54409.2022.9730387, Elsevier: Scopus)
16.	Zhuangzhuang Hao, Fuji Ren, XIN KANG, Ni Hongjun, Lv Shuaishuai and Wang Hui : Classification of Steel Strip Surface Defects Based on Optimized ResNet18, 2021 IEEE International Conference on Agents (ICA), 61-62, Dec. 2021. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICA54137.2021.00018 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85127619007 (DOI: 10.1109/ICA54137.2021.00018, Elsevier: Scopus)
17.	KAIXUAN WANG, Fuji Ren, XIN KANG, Shuaishuai Lv, Hongjun Ni and Yuan Haifeng : Thermal Defect Detection and Location for Power Equipment based on Improved VGG16, Proceedings of the 5th IEEE International Conference on Agent, Dec. 2021. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICA54137.2021.00014 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85127674002 (DOI: 10.1109/ICA54137.2021.00014, Elsevier: Scopus)
18.	Kubono Yusuke, Shun Nishide, XIN KANG and Fuji Ren : Prediction and Generation of Multiple Complex Drawing Figures From Partial Drawing Sequences, 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management, 1-5, Nov. 2021. (Link to Publication Site) ● Publication site (DOI): 10.1109/HNICEM54116.2021.9732036 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85127538609 (DOI: 10.1109/HNICEM54116.2021.9732036, Elsevier: Scopus)
19.	Liang Li, Min Hu, Fuji Ren and Haijun Xu : Temporal Attention Based TCN-BIGRU Model for Energy Time Series Forecasting, 2021 IEEE International Conference on Computer Science, Artificial Intelligence and Electronic Engineering (CSAIEE), 187-193, SC, USA, Aug. 2021. (Link to Publication Site) ● Publication site (DOI): 10.1109/CSAIEE54046.2021.9543210 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/CSAIEE54046.2021.9543210 (DOI: 10.1109/CSAIEE54046.2021.9543210)
20.	Kui Zhang, Min Hu, Fuji Ren and Pengyuan Hu : Sentiment Analysis of Chinese Product Reviews Based on BERT Word Vector and Hierarchical Bidirectional LSTM, 2021 IEEE International Conference on Computer Science, Artificial Intelligence and Electronic Engineering (CSAIEE), 9-14, SC, USA, Aug. 2021. (Link to Publication Site) ● Publication site (DOI): 10.1109/CSAIEE54046.2021.9543231 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/CSAIEE54046.2021.9543231 (DOI: 10.1109/CSAIEE54046.2021.9543231)
21.	Jing Wang, Fuji Ren and Yindong Dong : Application of Multiple Neural Networks in Aspect Sentiment Analysis, 2021 IEEE 6th International Conference on Cloud Computing and Big Data Analytics, 178-182, Chengdu, Apr. 2021. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICCCBDA51879.2021.9442548 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/ICCCBDA51879.2021.9442548 (DOI: 10.1109/ICCCBDA51879.2021.9442548)
22.	XIN KANG, Yunong Wu and Fuji Ren : TUA1 at the NTCIR-15 DialEval-1 Task, Proceedings of the 15th NTCIR Conference on Evaluation of Information Access Technologies, 53-56, Tokyo, Dec. 2020.
23.	Shi Xuefeng, XIN KANG, Liao Ping and Fuji Ren : Building Label-Balanced Emotion Corpus Based On Active Learning for Text Emotion Classification, In Proceedings of 2019 4th International Symposium on Artificial Intelligence and Robotics (ISAIR2019), 13-24, Nov. 2020. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85097405906 (Elsevier: Scopus)
24.	Weiwei Zhang and Fuji Ren : ELMo+Gated Self-attention Network Based on BiDAF for Machine Reading Comprehension, IEEE 11th International Conference on Software Engineering and Service Science (ICSESS), 1-6, Beijing, Oct. 2020. (Summary) Machine reading comprehension (MRC) has always been a significant part of artificial intelligence and the focus in the field of natural language processing (NLP). Given context paragraph, to answer its query, we need to encode complex interaction between the question and the context. In the late years, with the rapid progress of neural network model and attention theory, MRC has made great advances. Especially, attention theory has been widely used in MRC. However, the accuracy of the previous classic baseline model has some upside potential and some of them did not take into account the long context dependence and polysemy. In this paper, for resolving the above problems and further improve the model, we introduce ELMo representations and add a gated self-attention layer to the Bi-Directional Attention Flow network (BIDAF). In addition, we employ the feature reuse method and modify the linear function of answer layer to further improve the performance. In the experiment of SQuAD, we prove this model greatly exceeds the baseline BIDAF model and its performance is close to the average level of human test, which proves the validity of this model. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICSESS49938.2020.9237663 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85096179019 (DOI: 10.1109/ICSESS49938.2020.9237663, Elsevier: Scopus)
25.	Shota Inui, Fuji Ren, Shun Nishide and XIN KANG : Gait recognition in real environment using gait energy image generated by Mask R-CNN, 2020 IEEE International Conference on Mechatronics and Automation (ICMA), Beijing, China, Oct. 2020. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICMA49215.2020.9233582 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/ICMA49215.2020.9233582 (DOI: 10.1109/ICMA49215.2020.9233582)
26.	Liyuan Liang, Xiaodong Ji and Fuji Ren : Attention-based Bi-LSTM-CRF Network for Emotion Cause Extraction in Texts, 2020 IEEE International Conference on Mechatronics and Automation (ICMA), Beijing, China, Oct. 2020. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICMA49215.2020.9233688 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/ICMA49215.2020.9233688 (DOI: 10.1109/ICMA49215.2020.9233688)
27.	Quan Wang, Fei Wang, Peilin Jiang and Fuji Ren : Binary K-means Tree Ensemble Classifiers, The 15th International Conference on Natural Language Processing and Knowledge Engineering, Xian, China and Web, Oct. 2020.
28.	Wenjie Liu, Fuji Ren and Guoqing Wu : Multi-scale Receptive Field Fusion Residual Network for Image Classification, The 15th International Conference on Natural Language Processing and Knowledge Engineering, Xian, China and Web, Oct. 2020.
29.	Duo Feng and Fuji Ren : Real-time Dynamic Facial Expression Recognition System Based On CNN-GRU, The 15th International Conference on Natural Language Processing and Knowledge Engineering, Xian, China and Web, Oct. 2020.
30.	Kaixuan Wang, Hongjun Ni, Fuji Ren, Jiaqiao Zhang, Shuaishuai Lv and Xingxing Wang : Thermal Fault Area Recognition and Location System based on Infrared Image, The 15th International Conference on Natural Language Processing and Knowledge Engineering, Xian, China and Web, Oct. 2020.
31.	Kyoya Abe, Fuji Ren, Shun Nishide and XIN KANG : Construction of emergency medical support system based on understanding dialect intention, The 15th International Conference on Natural Language Processing and Knowledge Engineering, Xian, China and Web, Oct. 2020.
32.	Tianhao She and Fuji Ren : A humanoid robot based on neural network architecture for accompanying children with autism, The 15th International Conference on Natural Language Processing and Knowledge Engineering, Xian, China and Web, Oct. 2020.
33.	Siyuna Xue and Fuji Ren : Capsule Network with TC Loss for Intention Detection, The 15th International Conference on Natural Language Processing and Knowledge Engineering, Xian, China and Web, Oct. 2020.
34.	Jiawen Deng and Fuji Ren : Local Label Correlation Learning for Multi-Label Classification, The 15th International Conference on Natural Language Processing and Knowledge Engineering, Xian, China and Web, Oct. 2020.
35.	Rongyu Dou and Fuji Ren : Detecting Early Stage Depressions Based on Compound Neural Language Understanding, The 15th International Conference on Natural Language Processing and Knowledge Engineering, Xian, China and Web, Oct. 2020.
36.	Qian Zhang and Fuji Ren : Potential Preference Based Bayesian Personalized Ranking for One-Class Collaborative Filtering, The 15th International Conference on Natural Language Processing and Knowledge Engineering, Xian, China and Web, Oct. 2020.
37.	Ziyun Jiao and Fuji Ren : Improved of RelGAN for Text Generation, The 15th International Conference on Natural Language Processing and Knowledge Engineering, Xian, China and Web, Oct. 2020.
38.	Yuki Obayashi, Feni Betriana, Tetsuya Tanioka, Tomoya Yokotani, Ryuichi Tanioka, Chihiro Kawai, Hirokazu Ito, Yuko Yasuhara, Kyoko Osaka, Kazuyuki Matsumoto, Fuji Ren and Yoshihiro Kai : Development issues on communication robots' application in order to use for the older people care, The 15th NLPKE (NLPKE 2020), WEB, Oct. 2020.
39.	Fei Ding, XIN KANG, Shun Nishide, Guan Zhijin and Fuji Ren : A fusion model for multi-label emotion classification based on BERT and topic clustering, In International Symposium on Artificial Intelligence and Robotics 2020, Vol.11574, 98-111, Oct. 2020. (Link to Publication Site) ● Publication site (DOI): 10.1117/12.2579255 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1117/12.2579255 (DOI: 10.1117/12.2579255)
40.	Yokotani Tomoya, Tanioka Ryuichi, Kawai Chihiro, Betriana Feni, Hirokazu Ito, Yuko Yasuhara, Kazuyuki Matsumoto, Fuji Ren and Tetsuya Tanioka : Human operator's "Characteristic of autonomic nerve activity as psychological burden" and " Clarification of thinking process for AI development" while operating the humanoid robot conversation program, The 15th NLPKE (NLPKE 2020), WEB, Oct. 2020.
41.	LI Qianqian, Fuji Ren, Shen Xiaoyan and XIN KANG : Speech emotion recognition based on data enhancement in time-frequency domain, International Symposium on Artificial Intelligence and Robotics 2020, Vol.115740R, 234-241, Oct. 2020. (Link to Publication Site) ● Publication site (DOI): 10.1117/12.2579205 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85096352430 (DOI: 10.1117/12.2579205, Elsevier: Scopus)
42.	Liu Jia, XIN KANG, Shun Nishide and Fuji Ren : Collaborative filtering recommendation algorithm based on bisecting K-means clustering, In International Symposium on Artificial Intelligence and Robotics 2020, Vol.11574, 311-318, Oct. 2020. (Link to Publication Site) ● Publication site (DOI): 10.1117/12.2580026 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85096355579 (DOI: 10.1117/12.2580026, Elsevier: Scopus)
43.	Hirokazu Ito, Kazuyuki Matsumoto, XIN KANG, Tetsuya Tanioka, Yuko Yasuhara, Rozzano De Castro Locsin and Fuji Ren : Examination to develop the artificial intelligence through transforming tacit knowledge of nurses' dialogue for patients with dementia towards explicit knowledge, The 15th NLPKE (NLPKE 2020), WEB, Oct. 2020.
44.	jiaqiao zhang, XIN KANG, Hongjun Ni and Fuji Ren : Surface Defects Classification of Steel Strips based on Transfer Learning and Naive Bayes Model, Proceedings of The 15 th International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE20), 22-23, Oct. 2020.
45.	Masago Koji, Amo Mizuho, Shun Nishide, XIN KANG and Fuji Ren : Generation of Musical Scores from Chord Sequences Using Neurodynamic Model, International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, 638-648, Sep. 2020. (Link to Publication Site) ● Publication site (DOI): 10.1007/978-3-030-55789-8_55 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85091292688 (DOI: 10.1007/978-3-030-55789-8_55, Elsevier: Scopus)
46.	zheng liu, XIN KANG, Shun Nishide and Fuji Ren : A Chinese-Japanese Vowel Priority Lip Matching Scheme Based on Humanoid Robot Ren-Xin, In Proceedings of 2020 5th International Symposium on Artificial Intelligence and Robotics (ISAIR2020), Jun. 2020.
47.	Sumida Hiroaki, Fuji Ren, Shun Nishide and XIN KANG : Environment Recognition Using Robot Camera, 2020 5th IEEE International Conference on Big Data Analytics (ICBDA), 282-286, May 2020. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICBDA49040.2020.9101205 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/ICBDA49040.2020.9101205 (DOI: 10.1109/ICBDA49040.2020.9101205)
48.	Qian Chu, Min Hu, Xiaohua Wang, Yu Gu, Fuji Ren and Tian Chen : Facial Expression Recognition Based on Contextual Generative Adversarial Network, the 6th IEEE International Conference on Cloud Computing and Intelligence Systems(CCIS2019), Singapore, Dec. 2019. (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS48116.2019.9073699 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85085021746 (DOI: 10.1109/CCIS48116.2019.9073699, Elsevier: Scopus)
49.	Yu Gu, Xiang Zhang, Zhi Liu and Fuji Ren : WiFi-based Real-time Breathing and Heart Rate Monitoring during Sleep, IEEE Global Communications Conference (GLOBECOM), Waikoloa, HI, USA, Dec. 2019. (Link to Publication Site) ● Publication site (DOI): 10.1109/GLOBECOM38437.2019.9014297 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85081977686 (DOI: 10.1109/GLOBECOM38437.2019.9014297, Elsevier: Scopus)
50.	Xi Wan, Fuji Ren and Yong Deng : Using Inception-Resnet V2 for Face-based Age Recognition in Scenic Spots, Proceedings of 2019 6th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS2019), 159-163, Singapore, Dec. 2019. (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS48116.2019.9073696 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85085037308 (DOI: 10.1109/CCIS48116.2019.9073696, Elsevier: Scopus)
51.	Jiaqiao Zhang, Fuji Ren, Hongjun Ni, Zhenya Zhang and Kaixuan Wang : Research on Information Recognition of VAT Invoice Based on Computer Vision, Proceedings of 2019 6th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS2019), 126-130, Singapore, Dec. 2019. (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS48116.2019.9073749 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85085023059 (DOI: 10.1109/CCIS48116.2019.9073749, Elsevier: Scopus)
52.	Fei Ding, Zhijing Guan and Fuji Ren : A Fast Optimization Algorithm for Nearest Neighbor Architecture Based on Quantum Weight, Proceedings of 2019 6th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS2019), 73-78, Singapore, Dec. 2019. (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS48116.2019.9073740 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85085001936 (DOI: 10.1109/CCIS48116.2019.9073740, Elsevier: Scopus)
53.	Chen Haiyan, Liu Zheng, XIN KANG, Shun Nishide and Fuji Ren : Investigating voice features for Speech emotion recognition based on four kinds of machine learning methods, Proceedings of 2019 6th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS2019), 195-199, Singapore, Dec. 2019. (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS48116.2019.9073725 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/CCIS48116.2019.9073725 (DOI: 10.1109/CCIS48116.2019.9073725)
54.	Yasumura Ryosuke, Shun Nishide, XIN KANG and Fuji Ren : Constructing a Fundamental DevelopmentalDrawing Learning Model Using an Arm Robot, Proceedings of 2019 6th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS2019), 185-189, Singapore, Dec. 2019. (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS48116.2019.9073689 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/CCIS48116.2019.9073689 (DOI: 10.1109/CCIS48116.2019.9073689)
55.	Li Jiaen, Fuji Ren, Shun Nishide and XIN KANG : Character action recognition based on deep convolutional neural network and action sequence, Proceedings of 2019 6th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS2019), 149-153, Singapore, Dec. 2019. (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS48116.2019.9073735 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/CCIS48116.2019.9073735 (DOI: 10.1109/CCIS48116.2019.9073735)
56.	Lu Xin, XIN KANG, Shun Nishide and Fuji Ren : Object detection based on SSD-ResNet, Proceedings of 2019 6th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS2019), 89-92, Singapore, Dec. 2019. (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS48116.2019.9073753 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/CCIS48116.2019.9073753 (DOI: 10.1109/CCIS48116.2019.9073753)
57.	Dou Rongyu, Shun Nishide, Fuji Ren and XIN KANG : ExploringUncertain Samples through Active Learning To Enhance Text Emotion Classification, Proceedings of 2019 6th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS2019), 26-30, Singapore, Dec. 2019. (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS48116.2019.9073729 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/CCIS48116.2019.9073729 (DOI: 10.1109/CCIS48116.2019.9073729)
58.	Hu Junlin, XIN KANG, Shun Nishide and Fuji Ren : Text multi-label sentiment analysis based on Bi-LSTM, Proceedings of 2019 6th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS2019), 16-20, Singapore, Dec. 2019. (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS48116.2019.9073727 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/CCIS48116.2019.9073727 (DOI: 10.1109/CCIS48116.2019.9073727)
59.	Zhou Zheng, XIN KANG, Shun Nishide and Fuji Ren : Capture Important Information for Reading andReasoning by A Two-Pass Attention Mechanism in Dynamic Memory Network, Proceedings of 2019 6th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS2019), Dec. 2019.
60.	Yun Gao, Haitao Yu, XIN KANG and Fuji Ren : TUA1 at the TREC 2019: Deep Learning Track, Proceedings of 28th Text Retrieval Conference (TREC 2019), Vol.1250, 1-3, Nov. 2019. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85180130017 (Elsevier: Scopus)
61.	Fuji Ren : Advanced Intelligence in Big Education, The 1st World Science and Technology Development Forum, Beijing, Oct. 2019.
62.	Fuji Ren : Can artificial intelligence ride the vast wilderness of big education and big health?, Nanzhou University, Nanzhou, China, Sep. 2019.
63.	Fuji Ren : Big Intelligence Education and Big Intelligence Health, Tsuinghua University, Beijing, China, Sep. 2019.
64.	Zhou Yitao, Fuji Ren, Shun Nishide and XIN KANG : Facial Sentiment Classification Based on Resnet-18 Model, Proceedings of 2019 International Conference on Electronic Engineering and Informatics (EEI), 463-466, Sep. 2019. (Link to Publication Site) ● Publication site (DOI): 10.1109/EEI48997.2019.00106 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/EEI48997.2019.00106 (DOI: 10.1109/EEI48997.2019.00106)
65.	Zhou Yangyang, XIN KANG and Fuji Ren : TUA1 at ImageCLEF 2019 VQA-Med: a Classification and Generation Model based on Transfer Learning, Working Notes of CLEF (2019), Vol.2380, 1-7, Lugano, Sep. 2019. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85070500176 (Elsevier: Scopus)
66.	Fuji Ren : AI knows your own better than you, International Artificial Intelligence Education Forum, Hefei, China, Aug. 2019.
67.	Tao Hong, Xiao Sun, Feng Tian and Fuji Ren : Sentiment Classification and Personality Detection Via Galvanic Skin Response Based on Deep Learning Models, The 5th International Conference on Big Data Computing and Communications, 313-317, Qingdao, China, Aug. 2019. (Link to Publication Site) ● Publication site (DOI): 10.1109/BIGCOM.2019.00054 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85076101681 (DOI: 10.1109/BIGCOM.2019.00054, Elsevier: Scopus)
68.	Chuanzheng Wei, Xiao Sun, Feng Tian and Fuji Ren : Speech Emotion Recognition with Hybrid Neural Network, The 5th International Conference on Big Data Computing and Communications, 298-302, Qingdao, China, Aug. 2019. (Link to Publication Site) ● Publication site (DOI): 10.1109/BIGCOM.2019.00051 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85076102550 (DOI: 10.1109/BIGCOM.2019.00051, Elsevier: Scopus)
69.	Yuxiang Zhou, Ni Hongjun, Fuji Ren and XIN KANG : Face and Gender Recognition System Based on Convolutional Neural networks, Proceedings of 2019 IEEE International Conference on Mechatronics and Automation (ICMA), 1091-1095, Tianjin, Aug. 2019. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICMA.2019.8816192 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/ICMA.2019.8816192 (DOI: 10.1109/ICMA.2019.8816192)
70.	Fu Kangwei, Sun Ling, XIN KANG and Fuji Ren : Text Detection for Natural Scene based on MobileNet V2 and U-Net, Proceedings of 2019 IEEE International Conference on Mechatronics and Automation (ICMA), 1560-1564, Tianjin, Aug. 2019. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICMA.2019.8816384 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85072394301 (DOI: 10.1109/ICMA.2019.8816384, Elsevier: Scopus)
71.	Tang Jingwei, Yao Xingtian, XIN KANG, Shun Nishide and Fuji Ren : Position-Free Hand Gesture Recognition Using Single Shot MultiBox Detector Based Neural Network, Proceedings of 2019 IEEE International Conference on Mechatronics and Automation (ICMA), 2251-2256, Tianjin, Aug. 2019. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICMA.2019.8816203 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85072403779 (DOI: 10.1109/ICMA.2019.8816203, Elsevier: Scopus)
72.	Fuji Ren : On the evolution of artificial intelligence and its topics, Harbin Institute of Technology, Harbin, China, Jun. 2019.
73.	Zhou Yangyang, Liu Zheng, XIN KANG, Yunong Wu and Fuji Ren : TUA1 at the NTCIR-14 STC-3 Task, Proceedings of the 14th NTCIR Conference, 338-345, Jun. 2019.
74.	Lu Qingqing, Zhang Xiaomei, XIN KANG and Fuji Ren : Feature Fusion Based on Neural Image Captioning with Spatial Attention, Proceedings of 2019 the 9th International Workshop on Computer Science and Engineering (WCSE 2019), 195-200, Hong Kong, Jun. 2019. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85081102148 (Elsevier: Scopus)
75.	Lu Yitian, Jiang Ping, Shun Nishide, XIN KANG and Fuji Ren : Traffic Sign Recognition Based on Up-sampling Convolution, Proceedings of 2019 the 9th International Workshop on Computer Science and Engineering (WCSE 2019), 136-142, Hong Kong, Jun. 2019. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85081101925 (Elsevier: Scopus)
76.	Liu Zheng, Fuji Ren and XIN KANG : Research on the Effect of Different Speech Segment Lengths on Speech Emotion Recognition Based on LSTM, Proceedings of 2019 the 9th International Workshop on Computer Science and Engineering (WCSE 2019), 491-499, Hong Kong, Jun. 2019. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85081110971 (Elsevier: Scopus)
77.	Fuji Ren : Advanced Intelligence and Emotional Robot, Tongji University, Shanghai, China, May 2019.
78.	Mengmeng Huang, Jun Liu, Yu Gu, Yifan Zhang and Fuji Ren : Your WiFi Knows You Fall: A Channel Data-driven Device-free Fall Sensing System, the 53rd IEEE International Conference on Communications (ICC), Shanghai, May 2019. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICC.2019.8762032 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85070209623 (DOI: 10.1109/ICC.2019.8762032, Elsevier: Scopus)
79.	Fuji Ren : 5G's 5WH and 5G + AI usher in a life revolution, The Second International Workshop on 5G Networking Technologies, kunshan, China, May 2019.
80.	Fuji Ren : Artificial Intelligence and Emotional Robot, Nandong University, Nandong, China, Apr. 2019.
81.	Fuji Ren : Artificial Intelligence · Current Situation of Emotional Robot · Future Direction, University of Electronic Science and Technology of China, Chengdu, China, Apr. 2019.
82.	Fuji Ren : Direction of artificial intelligence in the next 30 years, Tongji University, Shanghai, China, Feb. 2019.
83.	Jinliang Guo, Fang Fang, Wei Wang and Fuji Ren : EEG Emotion Recognition Basedon Granger Causality and Caps Net Neural Network, Proceedings of 2018 5th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS2018), 47-52, Nanjing, Nov. 2018. (Summary) Emotion recognition is a very challenging task in the brain-computer interface field, and it is of great significance in medical, education, military, and other fields. The classification problem is the key to the field of emotion recognition research. In this paper, a classification model based on CapsNet neural network is proposed. By extracting the granger causality feature of original EEG signals, sparse group lasso algorithm is used for feature screening, and the obtained high-relevance feature subset is taken as the input of the network to achieve the final emotional classification. The experimental results show that by adjusting the model parameters and network structure, the constructed CapsNet neural network performs emotional classification on EEG signals, and obtains 88.09% and 87.37% average classification accuracy under valence and arousal emotion dimensions, compared with SVM and CNN. The classification system can obtain better results and significantly improve the performance of EEG emotional classification. This is the first time that CapsNet is applied to EEG emotional classification.
84.	Jinghan Xu, Fuji Ren and Yanwei Bao : EEG Emotion Classification Based On Baseline Strategy, Proceedings of 2018 5th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS2018), 43-46, Nanjing, Nov. 2018. (Summary) Electroencephalograph (EEG) emotional computing, as an important task of pattern recognition, has received more and more attention in recent years and is widely used in human-computer interaction, emotional computing and medical fields. Most researches have focused on finding particularly effective features and classifiers to achieve higher classification accuracy in some cases, while most methods are only effective under specific tasks or data and lack broad applicability. In this paper, we propose a novel baseline strategy that introducing emotional features to acquire a newly generated baseline and then, calibrate the individualized features in the emotional features, so that decrease the experimental errors and improve the versatility and effectiveness of the classification method. We performed a classification comparison experiment with baseline-strategy and no baseline-strategy on the DEAP dataset. The selected methods adopt different power spectral density (PSD) feature extraction methods and are classified by Support Vector Machine (SVM) and convolutional neural network (CNN) respectively. The results showed that the experiments with the baseline-strategy achieved better classification results. (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS.2018.8691174 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85064976517 (DOI: 10.1109/CCIS.2018.8691174, Elsevier: Scopus)
85.	ZiyunJiao Jiao, Yi Yang, Hairong Zhu and Fuji Ren : Realization and Improvement of Object Recognition System on Raspberry Pi 3B+, Proceedings of 2018 5th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS2018), 465-469, Nanjing, Nov. 2018. (Summary) This paper propose a lightweight convolution neural network based on the depthwise separable convolution and the improved Linear Bottlenecks block. Running time and space complexity of the model are reduced by designing the network structure carefully. The neural network model can run fluently on the device of ARM architecture to complete tasks such as object recognition and object detection. 20 categories of common objects in life from ImageNet are randomly selected to carry out recognition experiments on Raspberry Pi 3B+. The experimental results show that the Top1 accuracy of the model in the testing dataset can reach 91%, and the average recognition speed for 224*224 pixel images can reach 176ms. (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS.2018.8691297 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85064981799 (DOI: 10.1109/CCIS.2018.8691297, Elsevier: Scopus)
86.	Siyuan Xue and Fuji Ren : Dialogue Act Recognition for Open-Domain Based on Word-level Sequence Annotation with CRF, IEEE International Conference on Software Engineering and Service Science, 36-40, Beijing, Nov. 2018. (Summary) In dialogue system, natural language understanding has a huge impact on human-machine interaction. Moreover, natural language contains a huge amount of noise within its content because the short length and free format. From this aspect, the demand of this paper is to design the useful feature representations and verify these feature sets by searching suitable machine learning approaches. Besides, the dialogue acts as labels associate with utterance can be viewed as sequence labelling problem. Considering this situation, this paper provides a word-level sequence annotation method, which annotates dialogue structural information and semantic information to each word of utterance. Meanwhile, Linear-CRF is employed in this paper because it is able to natively capture constrains of hidden state sequence and obtain optimal probability, which is perfectly suit for sequence labeling task. Compared with proposed method, this paper uses the Bag-of-word model to present utterance as baseline. According to result, all the designed features outperform the feature in baseline, which indicates that the proposed method is useful for DA recognition task. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICSESS.2018.8663960 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85063602758 (DOI: 10.1109/ICSESS.2018.8663960, Elsevier: Scopus)
87.	Jiawen Deng and Fuji Ren : Text classification with keywords and co-occurred words in two-stream neural network, Proceedings of 2018 5th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS2018), 456-460, Nanjing, Nov. 2018. (Summary) In the task of text classification, the results are often affected by the sparseness of the corpus in a certain category. This paper proposed a Text classification method based on keywords and co-occurred words in two-stream neural network, in which the keywords are selected from training corpus, and the co-occurred words are chosen from external corpus, and they both are the input of the aid-stream of neural network, which is to enhance the category characteristics of representation vector in main-stream, especially for the category with less data distribution. The experiment results in Fudan University Corpus proved that the proposed method further improved the accuracy of the traditional GRU network. The proposed aid-stream based on keywords and co-occurred words is of great significance to the task of text classification and will provide method support for other natural language processing task. (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS.2018.8691302 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85064990328 (DOI: 10.1109/CCIS.2018.8691302, Elsevier: Scopus)
88.	Fuji Ren : Advanced AI and Its Future, IEEE CCIS and NLP-KE, Nanjing, Nov. 2018.
89.	Yu Gu, Yifan Zhang, Mengmeng Huang and Fuji Ren : Your WiFi Knows You Fall: A Channel Data Driven Device-free Fall Sensing System, Proceedings of 2018 5th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS), 943-947, Nanjing, Nov. 2018. (Summary) Falls are the second leading cause of injury deaths worldwide, inducing over $0.6$ million accidental deaths per year. Among various prevention strategies, fall-related research has been prioritized. However, conventional fall detection solutions relying on computer vision or wearable sensors embody several inherent limitations such as scalability, coverage, and privacy issues. To this end, we present FallSense, a transparent and real-time fall sensing system driven by wireless channel data. FallSense is built on a Dynamic Template Matching (DTM) algorithm, which can start with a light training set and keep updating on usage. FallSense has been realized on commodity WiFi devices and evaluated in real environments. Experimental results show that FallSense outperforms another state-of-the-art approach WiFall in terms of detection precision, false alarmrateand complexity. (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS.2018.8691181 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85064973861 (DOI: 10.1109/CCIS.2018.8691181, Elsevier: Scopus)
90.	Mengjia He and Fuji Ren : ADAPTIVE CONVERSATION SYSTEM BASED ON SCRIPT, Proceedings of 2018 5th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS), 562-566, Nanjing, Nov. 2018. (Summary) Our work is about conversationsystembased on script, supposing to design an adaptive agent. Purpose of this paper is to verify our idea of the transforming from text to image, and to implement an approach to find a new way of feature characterization on conversation text for our system. With sent2vec and SIFT, we designed a way of expression of text features and conducted experiments to classify conversation situations as Image Processing. Good results in close tests and bad results in open tests indicate the necessity of further work on our ideaandthe insignificanceofthe new feature characterization. (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS.2018.8691326 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85064983590 (DOI: 10.1109/CCIS.2018.8691326, Elsevier: Scopus)
91.	Duo Feng and Fuji Ren : Dynamic Facial Expression Recognition based on Two-Stream-CNN with LBP-TOP, Proceedings of 2018 5th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS), 355-359, Nanjing, Nov. 2018. (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS.2018.8691380 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85064987726 (DOI: 10.1109/CCIS.2018.8691380, Elsevier: Scopus)
92.	Kazuyuki Matsumoto, Manabu Sasayama, Minoru Yoshida, Kenji Kita and Fuji Ren : Transfer Learning Based on Utterance Emotion Corpus for Lyric Emotion Estimation, Proceedings of 2018 5th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS), 699-703, Nanjing, Nov. 2018. (Summary) In prior research, there are various emotion estimation approaches that are corpus-based, dictionary-based, or rule-based. However, it is necessary to prepare language resources suitable to each domain, which will incur substantial cost. In this paper, we propose an approach to estimate emotion of lyric phrase by using transfer learning. We applied the existing utterance emotion corpus to the lyric emotion estimation task. As the result of an evaluation experiment, we obtained higher accuracy than the baseline method using a simple bag of words feature tf-idf weighted vector and logistic regression model. (Keyword) Transfer learning / Emotion estimation / Lyric / Word embedding (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS.2018.8691207 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85064985706 (DOI: 10.1109/CCIS.2018.8691207, Elsevier: Scopus)
93.	Yoshie Setsu, XIN KANG, Shun Nishide and Fuji Ren : Emotion recognition for Twitter language based on lingual and expressional information, Proceedings of 2018 5th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS2018), 730-734, Nov. 2018. (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS.2018.8691222 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85064982962 (DOI: 10.1109/CCIS.2018.8691222, Elsevier: Scopus)
94.	Tianhao She, XIN KANG, Shun Nishide and Fuji Ren : Improving LEO Robot ConversationalAbility via Deep Learning Algorithms for 416 Children with Autism, Proceedings of 2018 5th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS2018), 416-420, Nov. 2018.
95.	XIN KANG, Yunong Wu and Fuji Ren : Progressively improving supervised emotion classification through active learning, Lecture Notes in Computer Science, Vol.11248, 49-57, Oct. 2018. (Link to Publication Site) ● Publication site (DOI): 10.1007/978-3-030-03014-8_4 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85057096653 (DOI: 10.1007/978-3-030-03014-8_4, Elsevier: Scopus)
96.	Fuji Ren : About emotional robots in responding to aging society, Japan-China Science and Technology Forum on the Aging Society by Utilizing ICT Technology, Qingdao, China, Oct. 2018.
97.	Fuji Ren : Facing the essence of artificial intelligence, 1 The 60th Anniversary Conference of Department of Computer Science and Technology of Tsinghua University, Beijing, China, Oct. 2018.
98.	Tian Chen, Chenxin Lin, Huaguo Liang and Fuji Ren : A Dictionary-Based Test Data Compression Method Using Tri-State Coding, IEEE 27th Asian Test Symposium, 528-533, Hefei, China, Oct. 2018. (Link to Publication Site) ● Publication site (DOI): 10.1109/ATS.2018.00019 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85060017717 (DOI: 10.1109/ATS.2018.00019, Elsevier: Scopus)
99.	Shun Nishide and Fuji Ren : Improvement of Developmental Drawing Imitation Using Recurrent Neural Network Through Incorporation of AVITEWRITE Model, Proceedings of IEEE International Conference on Systems, Man, and Cybernetics, 1-5, Oct. 2018. (Link to Publication Site) ● Publication site (DOI): 10.1109/SMC.2018.00009 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85062224762 (DOI: 10.1109/SMC.2018.00009, Elsevier: Scopus)
100.	Liu Ning, Zhou Zheng, XIN KANG and Fuji Ren : TUA1 at eRisk 2018, CEUR Workshop Proceedings (CEUR-WS.org), Vol.2125, 1-7, Sep. 2018. (Keyword) early risk detection / feature representation / CNN / LSTM
101.	Zhou Yangyang, XIN KANG and Fuji Ren : Employing Inception-Resnet-v2 and Bi-LSTM for Medical Domain Visual Question Answering, CEUR Workshop Proceedings (CEUR-WS.org), Vol.2125, 1-11, Sep. 2018. (Keyword) VQA-Med / Inception-Resnet-v2 / Bi-LSTM / Attention (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85051091321 (Elsevier: Scopus)
102.	Fuji Ren : Advanced intelligent robot, Xihua University, Chengdu, China, Sep. 2018.
103.	Bo Shu, Fuji Ren and Yanwei Bao : Investigating Lstm with k-Max Pooling for Text Classification, 2018 11th International Conference on Intelligent Computation Technology and Automation (ICICTA), Changsha, China, Sep. 2018. (Summary) For most deep learning practitioners, text classification is synonymous with recurrent networks and is tackled at word level. The presented study is demonstrated that word-level inputs are better than character-level inputs. We describe the proposed model that utilizes Spatial-Dropout1D, LSTM and k-max pool. Because the word of these representations is measured in a word similarity task, so SpatialDropout can reduce information redundancy; LSTM keep track of information over longer periods of time. k-max pooling keep more useful information. The proposed model is better than the strong baseline methods on six benchmark datasets for sentiment classification and topic categorization. The code will be open. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICICTA.2018.00015 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85057200894 (DOI: 10.1109/ICICTA.2018.00015, Elsevier: Scopus)
104.	Xinyue Cao, Xiao Sun and Fuji Ren : Speech Data Enhancement Based on hybrid Neural Network, Advances in Multimedia Information Processing PCM 2018, Vol.11164, No.3, 362-372, Hefei, Sep. 2018. (Link to Publication Site) ● Publication site (DOI): 10.1007/978-3-030-00764-5_33 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85054496768 (DOI: 10.1007/978-3-030-00764-5_33, Elsevier: Scopus)
105.	Fuji Ren : Advanced AI and Its Future, Intelligent robot and its industrialization, Shanghai, Sep. 2018.
106.	Fuji Ren : Progress of emotional robot, Harvard Medical School, Boston, MA, Sep. 2018.
107.	Fuji Ren : Progress of emotional robot and its application, Tongji University, Shanghai, China, Aug. 2018.
108.	Fuji Ren : Emotional interaction and intelligent robot, Shanghai Jiaotong University, Shanghai, Jun. 2018.
109.	Xudong Zhang, Guoqing Wu and Fuji Ren : Searching Audio-Visual Clips for Dual-mode Chinese Emotional Speech Database, First Asian Conference on Affective Computing and Intelligent Interaction, 1-6, Beijing, China, May 2018. (Link to Publication Site) ● Publication site (DOI): 10.1109/ACIIAsia.2018.8470387 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/ACIIAsia.2018.8470387 (DOI: 10.1109/ACIIAsia.2018.8470387)
110.	Minjia Li, Lun Xie, Zhiling Tan, Zhiliang Wang and Fuji Ren : Emotional Contagion System By Perceiving Human Emotion Based on Physiological Signals, First Asian Conference on Affective Computing and Intelligent Interaction, 1-6, Beijing, China, May 2018. (Link to Publication Site) ● Publication site (DOI): 10.1109/ACIIAsia.2018.8470348 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/ACIIAsia.2018.8470348 (DOI: 10.1109/ACIIAsia.2018.8470348)
111.	Xiao Sun, Xinmiao Chen, Zhengmeng Pei and Fuji Ren : Emotional Human Machine Conversation Generation Based on SeqGAN, First Asian Conference on Affective Computing and Intelligent Interaction, 1-6, Beijing, China, May 2018. (Link to Publication Site) ● Publication site (DOI): 10.1109/ACIIAsia.2018.8470388 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85055523684 (DOI: 10.1109/ACIIAsia.2018.8470388, Elsevier: Scopus)
112.	Xiaohua Wang, Muzi Peng, Min Hu, Chunhua Jin and Fuji Ren : Combination of valence-sensitive loss with restrictive center loss for facial expression recognition, 10th International Conference on Advanced Computational Intelligence, 528-533, Xiamen, China, Mar. 2018. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICACI.2018.8377514 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85049776050 (DOI: 10.1109/ICACI.2018.8377514, Elsevier: Scopus)
113.	Fuji Ren : Intellectual business society and Jobless society: Unclear power of artificial intelligence, 2017 GLOBAL UNMANNED SYSTEM CONFERENCE, Zhuhai, China, Dec. 2017.
114.	Fuji Ren : IQ and EQ for Evolutionary robot, Sichuan University, Chengdu, China, Dec. 2017.
115.	Ning Liu and Fuji Ren : Multi-label Emotion Computing Using Dense Neural Network Based on Distance Feature Represented Ren_CECps, The 12th International Conference on Natural Language Processing and Knowledge Engineering, Chengdu, China, Dec. 2017.
116.	Haowen Wang, Min Hu, Fuji Ren and Xiaohua Wang : An improved algorithm of human-robot interaction oriented text similarity calculation, The 12th International Conference on Natural Language Processing and Knowledge Engineering, Chengdu, China, Dec. 2017.
117.	Xiaohua Wang, Muzi Peng, Min Hu and Fuji Ren : Facial Expression Recognition with Convolutional Neural Networks Based on Joint Loss, The 12th International Conference on Natural Language Processing and Knowledge Engineering, Chengdu, China, Dec. 2017.
118.	Duo Feng and Fuji Ren : Selected LBP-TOP based Dynamic Facial Expression Recognition on Ren-VFEdb, The 12th International Conference on Natural Language Processing and Knowledge Engineering, Chengdu, China, Dec. 2017.
119.	Yu Gu, Yantong Wang, Tao Liu and Fuji Ren : Your WiFi Knows How You Feel: Leveraging Commodity WiFi Devices for Emotion Sensing, The 12th International Conference on Natural Language Processing and Knowledge Engineering, Chengdu, China, Dec. 2017.
120.	Fuji Ren : Emotion Robot and Advanced Intelligence, The 12th International Conference on Natural Language Processing and Knowledge Engineering, Chengdu, China, Dec. 2017.
121.	XIN KANG, Yunong Wu and Fuji Ren : Mining Actionable Intents to Facilitate Search Engine Users' Actions, Proceedings of The 12th International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE17), 343-351, Chengdu, Dec. 2017.
122.	Qianlu Huang, Fuji Ren, XIN KANG, Shun Nishide and Qiang Wang : Recognizing facial emotions in the video, Proceedings of The 12th International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE17), 316-327, Chengdu, Dec. 2017.
123.	Yuming Xu, Fuji Ren, XIN KANG, Shun Nishide and Ping Jiang : Human Pose Recognition in Robots Based on Angle of Joint Vector, Proceedings of The 12th International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE17), 304-315, Chengdu, Dec. 2017.
124.	Qian Zhang, Fuji Ren, XIN KANG, Shun Nishide, Shibing Zhang and Xiaoge Zhang : Building Emotional Corpus for Microblogging Emoticons, Proceedings of The 12th International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE17), 289-303, Chengdu, Dec. 2017.
125.	Jie Shen, Ziyun Jiao, Fuji Ren, XIN KANG, Shun Nishide, Suichun Qu and Yi Yang : Realization and Improvement of Robot Object Recognition, Proceedings of The 12th International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE17), 251-263, Chengdu, Dec. 2017.
126.	Yunong Wu, Kenji Kita, Kazuyuki Matsumoto, XIN KANG and Fuji Ren : Exploring the Relations Between Posts and Comments for Short Text Conversation, Proceedings of The 12th International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE17), 228-238, Chengdu, Dec. 2017.
127.	Ruixue Xia, Fuji Ren, XIN KANG and Shun Nishide : RESEARCH ON CONSTRUCTION AND ANALYSIS OF JAPANESE-CHINESE EMOTIONAL EXPRESSION CORPUS, Proceedings of The 12th International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE17), 216-223, Chengdu, Dec. 2017.
128.	Yasuda Tadayoshi, Yamashita Maki, Shun Nishide, XIN KANG and Fuji Ren : Learning Efficient Drawing Sequence Through Training of Recurrent Neural Network Model, Proceedings of The 12th International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE17), 65-76, Chengdu, Dec. 2017.
129.	Kazuyuki Matsumoto, Fuji Ren, Minoru Yoshida and Kenji Kita : Review Score Estimation Based on Transfer Learning of Different Media Review Data, Proceedings of The 12th International Conference on Natural Language Processing and Knowledge Engineering(NLP-KE'17), 185-199, Dec. 2017. (Summary) In this paper, we proposed a model to classify reviews based on review data of different media. Recently, researches have been actively made on transfer learning between different domains with various kinds of big data as a target. Evaluation expressions are usually different in different domains, and this becomes a barrier for reputation analysis. Users usually use different linguistic expressions to refer to the creative works of each media. For example, media such as "anime", "comics", "games" and "movies" have different terms or expressions to be described their creative works. These differences can be considered showing features of each medium and such differences should be found in other expressions as well as in evaluation expressions. We analyzed what effect such differences would cause to classication accuracy by conducting transfer learning between review data ofdifferent media. In this paper, we proved compatibility between original (pre-transferring) and target (post-transferring) media for each medium of the creative works by constructing a review classication model. As a result of evaluation experiments, we could more accurately estimate review score without using SO-Score for training of review fragment based on Long Short Term Memory (LSTM) than the SO-Score based method. (Keyword) review classification / transfer learning / Long Short-Term Memory / different media
130.	Yunong Wu, XIN KANG, Kenji Kita and Fuji Ren : TUA1 at NTCIR-13 Short Text Conversation 2 Task, Proceedings of the 13th NTCIR Conference on Evaluation of Information Access Technologies, 211-214, Tokyo, Dec. 2017.
131.	Mengjia He, XIN KANG and Fuji Ren : TUA1 at the NTCIR-13 OpenLiveQ Task, Proceedings of the 13th NTCIR Conference on Evaluation of Information Access Technologies, 105-107, Tokyo, Dec. 2017.
132.	Chao Li, XIN KANG and Fuji Ren : Medweb Task: Identify Multi-Symptoms from Tweets Based on Active Learning and Semantic Information, Proceedings of the 13th NTCIR Conference on Evaluation of Information Access Technologies, 75-80, Tokyo, Dec. 2017.
133.	XIN KANG, Yunong Wu and Fuji Ren : TUA1 at the NTCIR-13 Actionable Knowledge Graph Task: Sampling Related Actions from Online Searching, Proceedings of the 13th NTCIR Conference on Evaluation of Information Access Technologies, 346-353, Tokyo, Dec. 2017.
134.	Yanqiu Li, Fuji Ren and Min Hu : Facial Expression Recognition Based on Dynamic Fuzzy Density, The 3rd International Conference on Fuzzy Systems and Data Mining, Hualien, Taiwan, Nov. 2017.
135.	Fuji Ren : Mental Health Computing and Emotional Robots, Nanzhou University, Nanzhou, China, Nov. 2017.
136.	Xiao Sun, Man Lv, Changqin Quan and Fuji Ren : Improved Facial Expression Recognition Method Based on ROI Deep Convolutional Neutral Network, 7th International Conference on Affective Computing and Intelligent Interaction (ACII2017), 256-261, Texas, USA, Oct. 2017. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85047370786 (Elsevier: Scopus)
137.	Fuji Ren : Advanced Natural Processing, Tongji University, Shanghai, China, Oct. 2017.
138.	Xiaohua Wang, Chen Xia, Min Hu and Fuji Ren : Facial Expression Recognition under Partial Occlusion Based on Fusion of Global and Local Features, The 9th International Conference on Graphic and Image Processing, Qingdao, China, Oct. 2017. (Link to Publication Site) ● Publication site (DOI): 10.1117/12.2303417 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85046427310 (DOI: 10.1117/12.2303417, Elsevier: Scopus)
139.	Yanqiu Li, Fuji Ren and Min Hu : A Fusion Decision Method Based on the Dynamic Fuzzy Density Assignment, 2017 International Conference on Advances in Image Processing, 28-32, Bangkok, Thailand, Aug. 2017. (Link to Publication Site) ● Publication site (DOI): 10.1145/3133264.3133283 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85033555795 (DOI: 10.1145/3133264.3133283, Elsevier: Scopus)
140.	Fuji Ren : Affective Computing and Emotional Robot, Beijing University of Posts and Telecommunications, Beijing, China, Aug. 2017.
141.	Xiao Sun, Xiaoqi Peng, Fuji Ren and Yun Xue : Human-Machine Conversation Based on Hybrid Neural Network, Computational Science and Engineering (CSE) and Embedded and Ubiquitous Computing (EUC), 2017 IEEE International Conference on, 1-11, Guangzhou, China, Jul. 2017. (Summary) With the rise and popular of artificial intelligence,the technology of conversation between human and machine get more and more attention. Using neural network model on the Encoder-Decoder framework has been wildly used in translation and human-machine conversation. This paper we propose a new hybrid neural network model (HNN) which consists of some essential neural network models (that is RNN, LSTM, and CNN). At the same time, according to the number of words that each sentence contains, we will get three sub-datasets from the original dataset. Then training and testing our models on different sub-datasets. Experimental results show that the best accuracy belongs to different hybrid models on different sub-datasets, which indicate the proposed approach can make use of each models advantages aim at different sub-dataset. (Keyword) 俗語 / トピック分析 / 時系列分析 (Link to Publication Site) ● Publication site (DOI): 10.1109/CSE-EUC.2017.54 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/CSE-EUC.2017.54 (DOI: 10.1109/CSE-EUC.2017.54)
142.	Zhao Han, Duoqian Miao, Fuji Ren and Hongyun Zhang : Discernibility Matrix and Rules Acquisition Based Chinese Question Answering System, Lecture Notes in Computer Science (Conference: International Joint Conference on Rough Sets), 239-248, OLSZTYN, Poland, Jul. 2017. (Summary) Different from English processing, Chinese text processing starts from word segmentation, and the results of word segmentation will influence the outcomes of subsequent processing especially in short text processing. In this paper, we introduce a novel method for Short Text Information Retrieval based Chinese Question Answering. It is developed from the Discernibility Matrix based Rules Acquisition method. Based on the acquired rules, the matching patterns of the training QA pairs can be represented by the reduced attribute words, and the words can also be represented by the QA patterns. Then the attribute words in the test QA pairs can be used to calculate the matching scores. The experimental results show that the proposed representation method of QA patterns has good flexibility to deal with the uncertainty caused by the Chinese word segmentation, and the proposed method has good performance at both MAP and MRR on the test data. (Link to Publication Site) ● Publication site (DOI): 10.1007/978-3-319-60837-2_20 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85022336430 (DOI: 10.1007/978-3-319-60837-2_20, Elsevier: Scopus)
143.	Fuji Ren : Affective Computing and Intelligent Robots, 2017 World Intellgence Conference, Tianjin, China, Jun. 2017.
144.	Shuda Xin, Yang Cao and Fuji Ren : Numerical simulation of VAWT on the effects of rotation cylinder, ACMME 2017 5th Asia Conference on Mechanical and Materials Engineering, No.99, 1-5, Tokyo, Japan, Jun. 2017. (Tokushima University Institutional Repository) ● Metadata: 115236 (Link to Publication Site) ● Publication site (DOI): 10.1088/1757-899X/207/1/012085 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1088/1757-899X/207/1/012085 (Tokushima University Institutional Repository: 115236, DOI: 10.1088/1757-899X/207/1/012085)
145.	Yu Gu, Jianwen Tian, Liwen Zhang, Zhi Liu, Fuji Ren and Xiaoyan Wang : Activity Recognition via Channel Response: From Theoretical Analysis to Real-world Experiments, IEEE 85th Vehicular Technology Conference: VTC2017-Spring, Toronto, Jun. 2017. (Link to Publication Site) ● Publication site (DOI): 10.1109/VTCSpring.2017.8108185 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85040554059 (DOI: 10.1109/VTCSpring.2017.8108185, Elsevier: Scopus)
146.	Yu Gu, Jinhai Zhan, Fuji Ren and Xiaoyan Wang : ``Silence is Golden'': Exploring Ambient Signals for Detecting Motions in a Real-time Manner, IEEE VTC-fall 2017 (IEEE 86th Vehicular Technology Conference), Toronto, Jun. 2017. (Link to Publication Site) ● Publication site (DOI): 10.1109/VTCFall.2017.8288264 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85045244300 (DOI: 10.1109/VTCFall.2017.8288264, Elsevier: Scopus)
147.	Fuji Ren : Health Computing and Emotional Robots, Xi'an Fourth Military Medical University, Xian, China, Mar. 2017.
148.	Fuji Ren : Mental Health Computing and Emotional Robotic, The Fourth Military Medical Universit, Xian, China, Mar. 2017.
149.	Changqin Quan, Lei Hua, Xiao Sun and Fuji Ren : Improve question type classification by integrating rich representation through neural networks, The 11th International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE'16), Okinawa, Dec. 2016.
150.	Yindong Dong, Fuji Ren, Fang Fang and Wei Wang : An improved clustering algorithm for EEG-based Emotion feature selection, The 11th International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE'16), Okinawa, Dec. 2016.
151.	Kai Yang, Quan Shi and Fuji Ren : Speech emotion recognition based on MFCC and D-MFCC, The 11th International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE'16), Okinawa, Dec. 2016.
152.	Shuda Xing, Yang Cao and Fuji Ren : Human-robot emotion interaction via human skeleton tracking, The 11th International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE'16), Okinawa, Dec. 2016.
153.	Penlin Jiang, Ziqin Wang, Fei Wang, Xuetao Zhang and Fuji Ren : Salient Object Detection from Global to Local, The 11th International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE'16), Okinawa, Dec. 2016.
154.	Zhichao Cui, Yuehu Liu and Fuji Ren : Integration of Homography Constraints and Feature Correspondences in the Image Sequences for Traffic Sign Localization, The 11th International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE'16), Okinawa, Dec. 2016.
155.	Xun Feng, Hongjun Ni and Fuji Ren : Voice conversion based on RBF neural network, The 11th International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE'16), Okinawa, Dec. 2016.
156.	Jiawen Deng, Mingyu Huang and Fuji Ren : Text classification based on word co-occurrence with background knowledge, The 11th International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE'16), Okinawa, Dec. 2016.
157.	Hiroki Urakami, Shun Nishide and Fuji Ren : Towards a Developmental Human-Robot Interaction System Using Robot Facial Expressions From Human Feedback, The 11th International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE'16), Okinawa, Dec. 2016.
158.	Shun Nishide, Hidenobu Shibasaki, XIN KANG and Fuji Ren : Generation of Humanlike Facial Expression for Natural Human-Robot Interaction System, The 11th International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE'16), Okinawa, Dec. 2016.
159.	Xiao Sun, Man Lv, Changqin Quan, Fang Tian and Fuji Ren : Facial Expression Recognition Based on Hybrid Deep-learning and Shallow Features, The 11th International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE'16), Okinawa, Dec. 2016.
160.	Chao Li and Fuji Ren : Classification of Biological Contacts and Crystal Contacts Using Deep Learning Model, The 11th International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE'16), Okinawa, Dec. 2016.
161.	XIN KANG, Yunong Wu and Fuji Ren : Disambiguating Users' Temporal Intent in Search Queries with Deep Neural Networks, The 11th International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE'16), 1, Okinawa, Dec. 2016.
162.	Fuji Ren : Advanced Intelligence and Multisource Imaging Model, The 11th International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE'16), Okinawa, Dec. 2016.
163.	Kazuyuki Matsumoto, Tanaka Satoshi, Minoru Yoshida, Kenji Kita and Fuji Ren : Ego-state Estimation from Short Texts Based on Sentence Distributed Representation, The 11th International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE'16), Dec. 2016. (Keyword) ego-state / egogram / deep neural network / sentence distributed representation
164.	Yang Wang, Shuibing He, Fuji Ren, Lujia Wang and Changzhong Xu : On Autonomous Service Migrations in the Cloud for Mobile Accesses, Parallel and Distributed Systems (ICPADS), 2016 IEEE 22nd International Conference on, Las Vegas, Dec. 2016. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICPADS.2016.0103 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/ICPADS.2016.0103 (DOI: 10.1109/ICPADS.2016.0103)
165.	Fuji Ren : Affective Computing and Human Robot Interaction, Peking University Shenzhen Graduate School, Nov. 2016.
166.	Fenfen Chen, Lujia Wang, Jue Lu, Fuji Ren, Yang Wang, Xi Zhang and Changzhong Xu : A Smart Cloud Robotic System Based on Cloud Computing Services, Cloud Computing and Big Data (CCBD), 2016 7th International Conference on, Macau, China, Nov. 2016. (Summary) In this paper, we present a smart service robotic system based on cloud computing services. The design and implementation of infrastructure, computation components and communication components are introduced. The proposed system can alleviate the complex computation and storage load of robots to cloud and provide various services to the robots. The computation components can dynamically allocate resources to the robots. The communication components allow easy access of the robots and provide flexible resource management. Furthermore, we modeled the task-scheduling problem and proposed a max-heaps algorithm. The simulation results demonstrate that the proposed algorithm minimized the overall task costs. (Link to Publication Site) ● Publication site (DOI): 10.1109/CCBD.2016.069 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/CCBD.2016.069 (DOI: 10.1109/CCBD.2016.069)
167.	Fuji Ren : On measures against aged society based on advanced intelligence, 2, Nov. 2016.
168.	Fuji Ren : IQ and EQ of The future robot, World Robot Conference 2016, Oct. 2016.
169.	Fuji Ren : Robot Evolution and Humanitarian Intelligence, Institute of Automation, Chinese Academy of Sciences, Oct. 2016.
170.	Zhong Huang, Fuji Ren and Yanwei Bao : Human-like facial expression imitation for humanoid robot based on recurrent neural network, International Conference on Advanced Robotics and Mechatronics (ICARM),, Aug. 2016. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICARM.2016.7606937 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84999007053 (DOI: 10.1109/ICARM.2016.7606937, Elsevier: Scopus)
171.	Yanqiu Li, Fuji Ren and Min Hu : Facial Expression Recognition based on DT-CWT and Weighted Inverse Cloud Model, Modelling, Simulation and Identification / 841: Intelligent Systems and Control, Campinas, Brazil, Aug. 2016. (Link to Publication Site) ● Publication site (DOI): 10.2316/P.2016.841-010 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.2316/P.2016.841-010 (DOI: 10.2316/P.2016.841-010)
172.	Inoue Yuta, Shun Nishide and Fuji Ren : Facial Expression Recognition Adaptive to Face Pose Using RGB-D Camera, Springer International Publishing Switzerland, IEA/AIE 2016, Vol.LNAI 9799, 422-427, Aug. 2016. (Link to Publication Site) ● Publication site (DOI): 10.1007/978-3-319-42007-3_36 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84978832852 (DOI: 10.1007/978-3-319-42007-3_36, Elsevier: Scopus)
173.	Bin Zhang, Changqin Quan and Fuji Ren : Study on CNN in the recognition of emotion in audio and images, Computer and Information Science (ICIS), 2016 IEEE/ACIS 15th International Conference on, 319-323, Okayama, Japan, Jun. 2016. (Summary) In this paper, the performance of Convolution Neural Network (CNN) in image recognition and emotion recognition in speech will be compared and presented. Feature extraction and selection in pattern recognition is an important issue and have been frequently discussed. Moreover, two-dimensional signals such as image and voice are hard to be modelled well by traditional models like SVM. The ability of CNN to characterize two-dimensional signals is prominent. And CNN can adaptively extract feature to eliminate the dependence on human subjectivity or experience. It mimics the effect of local filtering in visual cortex cells to dig local correlation in natural dimensional space. In this work, for the problems of the image recognition and emotion recognition in speech, CNN and SVM which is used as baseline for comparison of the recognition effect. Different kernel functions in SVM have been experimented for image recognition with, the best accuracy is 94.17%. However, the accuracy of using CNN is 95.5% (7291 pictures for train and 2007 pictures for test) with less time consuming. In the emotion recognition of speech, the accuracy of CNN is 97.6% corresponds to 55.5% by baseline model (4000 utterances for training, 1500 for validation, 500 for test). The experimental results showed that CNN can effectively extract features and its modeling capability for two-dimensional signals is prominent. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICIS.2016.7550778 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/ICIS.2016.7550778 (DOI: 10.1109/ICIS.2016.7550778)
174.	Ning Liu, Mengjia He, Chao Li, XIN KANG and Fuji Ren : TUTA1 at the NTCIR-12 Temporalia Task, Proceedings of the 12th NTCIR Conference on Evaluation of Information Access Technologies, 258-261, Tokyo, Jun. 2016. (Keyword) temporal search / relation extraction / similarity computing
175.	XIN KANG, Yunong Wu and Fuji Ren : KGO at the NTCIR-12 Temporalia Task: Exploring Temporal Information in Search Queries, Proceedings of the 12th NTCIR Conference on Evaluation of Information Access Technologies, 247-252, Tokyo, Jun. 2016.
176.	XIN KANG and Fuji Ren : Understanding Blog author's emotions with hierarchical Bayesian models, 2016 IEEE 13th International Conference on Networking, Sensing, and Control (ICNSC), 1-6, Mexico City, Mexico, May 2016. (Summary) The research of inferring emotions in natural language is confronted with two major challenges: the lack of basic knowledge in emotion expressions and the co-occurrence of separate emotions through all language unites. In this paper, we propose a Bayesian inference method to explore the basic knowledge with respect to emotion expression in different semantic dimensions, and to infer the co-occurrence of multiple emotion labels through words to the document. Specifically, we incorporate emotions and semantic dimensions as the latent factors in determining the distribution of observed words in a corpus of Blog articles. For each Blog article, we further generalize emotions from words to the document by incorporating a document specific hierarchy in the emotion distributions. The basic knowledge and co-occurred emotion labels in words and documents are obtained through a Gibbs sampling inference. Our experiment is performed on the well-developed Chinese emotion corpus, i.e. Ren-CECps, which indicates both higher accuracy and better robustness in our word and document emotion predictions compared with those generated by the state-of-the-art emotion prediction algorithms, and demonstrates a distribution of emotions in different word semantic dimensions. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICNSC.2016.7479037 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84978085764 (DOI: 10.1109/ICNSC.2016.7479037, Elsevier: Scopus)
177.	Yu Gu, Lianghu Quan, Fuji Ren and Jie Li : Optimal parameter setting for indoor localization via big data analysis, Computer Communications Workshops (INFOCOM WKSHPS), 2016 IEEE Conference on, 1-6, San Francisco, CA, USA, Apr. 2016. (Summary) Indoor localization remains a hot topic and receives tremendous research efforts during the last few decades. While most previous efforts focus on the designing issue, little effort has been paid to the impact of different environmental parameters on the system performance. To this end, we present an extensive empirical study with real-world experiments to provide sufficient data for analysis. By seizing the fundamental relationship between a given scenario and environmental parameters, we show that the optimal parameter settings can be achieved for the scenario regardless of the localization algorithms. (Link to Publication Site) ● Publication site (DOI): 10.1109/INFCOMW.2016.7562139 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/INFCOMW.2016.7562139 (DOI: 10.1109/INFCOMW.2016.7562139)
178.	Yu Gu, Mengni Chen, Fuji Ren and Jie Li : Handling Environmental Dynamics in Indoor WiFi Fingerprint Localization, 2016 IEEE Wireless Communications and Networking Conference (WCNC), 1-6, Doha, Qatar, Apr. 2016. (Link to Publication Site) ● Publication site (DOI): 10.1109/WCNC.2016.7565019 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84989844050 (DOI: 10.1109/WCNC.2016.7565019, Elsevier: Scopus)
179.	Fuji Ren : Alpha GO and the emotional robot, Tongji University, Mar. 2016.
180.	Fuji Ren : Emotional Robots with human-computer symbiosis, Nantong University, Mar. 2016.
181.	Chao Li, Fuji Ren and XIN KANG : Verb-object Selectional Preferences in Chinese Based on Distributional Semantic Model, 18th International Conference on Mathematical Methods, Computational Techniques and Intelligent Systems (MAMECTIS '16), 59-62, Venice, Italy, Jan. 2016. (Summary) In this paper, we propose a approach based on distributional semantic model on selectional preference task in the verb & dobj (direct object) relationship. The distributional representations of words are employed as the semantic feature by using the Word2Vec algorithm. Experimental results show that the proposed approach is effective to discriminate the compatibility of the object words and the performance could be improved by increasing the number of training data. Moreover, the results demonstrate that the semantics is an universal, effective and stable feature in this task, which is consistent with our awareness of using words.
182.	Duo Feng, Shun Nishide and Fuji Ren : Automatic Facial Feature Points Extraction and Expression Recognition Based on Video Database, Proceedings of 4th National Conference on Electrical, Electronics and Computer Engineering, 1525-1530, Dec. 2015. (Summary) In this paper, we propose a facial expression recognition method using Support Vector Machine on mapped coordinate sequence features. The proposed system is almost fully automatic, in which landmark initialization is based on general knowledge with edge information, and missing information compensation is done by ASM. The geometric features of facial expressions were extracted from sequences of facial landmarks. Validation experiments were conducted using facial expression sequences extracted from a video based facial expression database. (Keyword) 感情コーパス / 感情推定 / タグ付き対訳コーパス
183.	Fuji Ren : About the EQ of Robot, Invited Speech The New Era of Robots Brought by Artificial Intelligence, China National Convention Center, Nov. 2015.
184.	Xiao Sun, Jiaqi Ye and Fuji Ren : Hybrid Model Based Influenza Detection with Sentiment Analysis from Social Network, Procedings of 4th Natioal Conference on Social Media Processing, 51-62, Guangzhou, China, Nov. 2015.
185.	Kazuyuki Matsumoto, Minoru Yoshida, Kenji Kita and Fuji Ren : An Approach to Refine Translation Candidates for Emotion Estimation in Japanese-English Language, Proceedings of the 7th International Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, Vol.2, 74-83, Nov. 2015. (Summary) Researches on emotion estimation from text mostly use machine learning method. Because machine learning requires a large amount of example corpora, how to acquire high quality training data has been discussed as one of its major problems. The existing language resources include emotion corpora; however, they are not available if the language is different. Constructing bilingual corpus manually is also financially difficult. Wepropose a method to convert a training data into different language using an existing Japanese-English parallel emotion corpus. With a bilingual dictionary, the translation candidates are extracted against every word of each sentence included in the corpus. Then the extracted translation candidates are narrowed down into a set of words that highly contribute to emotion estimation and we used the set of words as training data. As theresult of the evaluation experiment using the training data created by our proposed method, the accuracy of emotion estimation increased up to 66.7% in Naive Bayes. (Keyword) Emotion Corpus / Emotion Estimation / Bilingual Tagged Corpus
186.	Fuji Ren : Keynote Speech Natural Language Understanding and Affective Computing, the 10th International Conference on Natural Language Processing and Knowledge Engineering, Oct. 2015.
187.	Yu Gu, Lianghu Quan and Fuji Ren : Towards An Optimal Parameter Setting for Indoor Localization: An Empirical Study, the 10th International Conference on Natural Language Processing and Knowledge Engineering, Sapporo, Japan, Oct. 2015.
188.	Kazuyuki Matsumoto, Minoru Yoshida, Seiji Tsuchiya, Kenji Kita and Fuji Ren : Slang Analysis Based on Variant Information Extraction Focusing on the Time Series Topics, the 10th International Conference on Natural Language Processing and Knowledge Engineering, Sapporo, Japan, Oct. 2015.
189.	Shihui Zhao, Xiao Sun, Fuji Ren and Fang Tian : Distinguish human translation and machine translation based on hybrid model, the 10th International Conference on Natural Language Processing and Knowledge Engineering, Sapporo, Japan, Oct. 2015.
190.	Lei Hua, Changqin Quan and Fuji Ren : A hybrid kernel based method for relation extraction and gene-disease interaction network construction, the 10th International Conference on Natural Language Processing and Knowledge Engineering, Sapporo, Japan, Oct. 2015.
191.	Bin Zhang, Changqin Quan and Fuji Ren : Improvements in Convolutional Neural Network for Recognizing Emotion in Speech, the 10th International Conference on Natural Language Processing and Knowledge Engineering, Sapporo, Japan, Oct. 2015.
192.	Xiaohua Wang, Dengyong Hou, Min Hu and Fuji Ren : Dual-modality emotion recognition of facial expressions and gestures, the 10th International Conference on Natural Language Processing and Knowledge Engineering, Sapporo, Japan, Oct. 2015.
193.	Yanqiu Li, Fuji Ren, Lianfeng Xu, Min Hu and Zixi Yu : Face Recognition Based on ULBP and BP Neural Network, the 10th International Conference on Natural Language Processing and Knowledge Engineering, Sapporo, Japan, Oct. 2015.
194.	Min Hu, Xiaoyin Huang, Fuji Ren and Xiaohua Wang : Facial expression recognition based on MBP and sparse representation, the 10th International Conference on Natural Language Processing and Knowledge Engineering, Sapporo, Japan, Oct. 2015.
195.	Jiaqi Ye, Xiao Sun, Fuji Ren and Fang Tian : Real Time Influenza Detection based on Discriminative Model with Emotional Factors from Social Networks, the 10th International Conference on Natural Language Processing and Knowledge Engineering, Sapporo, Japan, Oct. 2015.
196.	Xiao Sun, Fei Gao, Chengcheng Li and Fuji Ren : Chinese Microblog Sentiment Classification Based on Convolution Neural Network with Content Extension Method, Proceedings of the 6th International Conference on Affective Computing and Intelligent Interaction (ACII2015), 408-414, Xi'an, Sep. 2015. (Summary) Related research for sentiment analysis on Chinese microblog is aiming at analyzing the emotion of posters. This paper presents a content extension method that combines post with its' comments into a microblog conversation for sentiment analysis. A new convolutional auto encoder which can extract contextual sentiment information from microblog conversation of the post is proposed. Furthermore, a DBN model, which is composed by several layers of RBM(Restricted Boltzmann Machine) stacked together, is implemented to extract some higher level feature for short text of a post. These RBM layers can encoder observed short text to learn hidden structures or semantics information for better feature representation. A ClassRBM (Classification RBM) layer, which is stacked on top of RBM layers, is adapted to achieve the final sentiment classification. The experiment results demonstrate that, with proper structure and parameter, the performance of the proposed deep learning method on sentiment classification is better than state-of-the-art surface learning models such as SVM or NB, which also proves that DBN is suitable for short-length document classification with the proposed feature dimensionality extension method. (Keyword) Social Network / Microblog Conversation / Sentiment Analysis
197.	Kazuyuki Matsumoto, Kyosuke Akita, Minoru Yoshida, Kenji Kita and Fuji Ren : Estimate the Intimacy of the Characters Based on Their Emotional States for Application to Non-Task Dialogue, Proceedings of the 6th International Conference on Affective Computing and Intelligent Interaction (ACII2015), 327-333, Xi'an, Sep. 2015. (Summary) Non-task-oriented dialogue requires someschemes that enable smooth and flexible conversations with auser. For example, it would be possible to go beyond the closedrelationship between the system and the user by consideringthe users relationship with others in real life. In this paper,we focused on the dialogue made by the two characters in adrama scenario, and tried to express their relationship with ascale of intimacy degree. There will be such various elementsrelated to the intimacy degree as the frequency of response to theutterance and the attitude of a speaker during the dialogue. Wefocused on the emotional state of the speaker during the utteranceand tried to realize intimacy estimation with higher accuracy. Asthe evaluation result, we achieved higher accuracy in intimacyestimation than the existing method based on speech role. (Keyword) Intimacy Estimation / Scenario Corpus / Emotion Recognition (Link to Publication Site) ● Publication site (DOI): 10.1109/ACII.2015.7344591 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84964027376 (DOI: 10.1109/ACII.2015.7344591, Elsevier: Scopus)
198.	Xiaoming Xu, Changqin Quan and Fuji Ren : Facial Expression Recognition based on Gabor Wavelet Transform and Histogram of Oriented Gradients, Proceedings of 2015 IEEE International Conference on Mechatronics and Automation, 2117-2122, Beijing, China, Aug. 2015. (Summary) In order to get more effective expression features,this paper proposes an approach based on Gabor feature andHistogram of Oriented Gradients (HOG). Gabor Wavelet filter isfirst used as preprocessing stage for feature extraction. Handingthe characteristics with a large number of dimensions, binaryencoding (BC) is applied for dimensionality reduction.Dimensionality of the feature vector is reduced by using HOGalgorithm. Experiments were performed on Cohn-Kanade facialexpression database and the support vector machine classifier isused for expression classification. We obtained experimentalresults with an average recognition rate of 92.5%, which revealsthat the proposed method is superior to other Gabor Wavelettransform based approaches under the same experimentalenvironment. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICMA.2015.7237813 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84955326914 (DOI: 10.1109/ICMA.2015.7237813, Elsevier: Scopus)
199.	Zhao Han, Fuji Ren and Duoqian Miao : A SYNTHETIC AND COMPUTIONAL LANGUAGE MODEL FOR INTERACTIVE DIALOGUE SYSTEM, Proceedings of International Conferences Intelligent Systems and Agents 2015, 73-80, Las Palmas de Gran Canaria, Spain, Jul. 2015.
200.	Tian Chen, Xin Yi, Wei Wang, Jun Liu, Huaguo Liang and Fuji Ren : Low Power Multistage Test Data Compression Scheme, Proceedings of CFTC2015, 66-72, Jul. 2015.
201.	Hirokazu Ito, Kazuyuki Matsumoto, Misao Miyagawa, Yumi Kuwamura, Yuko Yasuhara, Fuji Ren, Tetsuya Tanioka and Rozzano De Castro Locsin : Professional Nurses Attitudes Towards the Introduction of Humanoid Nursing Robots (HNRs) to the Hospital, International Association for Human Caring 36th International Conference, New Orleans, May 2015.
202.	Lei Hua, Changqin Quan and Fuji Ren : Gene-disease Relation Extraction and Gene Interaction Network Construction, Proceedings of 7th International Conference on Bioinformatics and Computational Biology, 1-8, Mar. 2015.
203.	Yu Gu, Lianghu Quan, Fuji Ren and Jie Li : Fast Indoor Localization of Smart Hand-held Devices Using Bluetooth, Mobile Ad-hoc and Sensor Networks (MSN), 2014 10th International Conference on, 186-194, Maui, Hawaii USA, Dec. 2014. (Summary) Indoor localization remains a hot topic during the last few decades. Previous research mainly relies on wireless fingerprints and thus demands a large number of APs or labor-intensive site survey. To this end, by exploring Bluetooth features and leveraging user motions, we introduce a novel localization scheme that needs neither APs nor site survey. More specifically, through a systematic experimental study, we gain in-depth understandings of Bluetooth characteristics e.g., The impact of various factors such as distance, orientation, and obstacles on the Bluetooth RSSI (Received Signal Strength Indicator). With the empirical experiences, a novel motion-assisted localization model is built to describe the relationship between RSSI and device location. Based on the model, we design a localization scheme that iteratively adjusts the search directions according to RSSI changes to approach the target device. We prototype and evaluate our system in several real-world scenarios. Extensive experiments show that the proposed scheme is efficient in terms of localization accuracy, searching time and energy consumption. (Link to Publication Site) ● Publication site (DOI): 10.1109/MSN.2014.32 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/MSN.2014.32 (DOI: 10.1109/MSN.2014.32)
204.	Yu Haitao, XIN KANG and Fuji Ren : TUTA1 at the NTCIR-11 Temporalia Task, Proceedings of the 11th NTCIR Conference, 461-467, Dec. 2014.
205.	Haitao Yu, Xin Kang and Fuji Ren : TUTA1 at the NTCIR-11 Temporalia Task, The 11th NTCIR Conference, 461-467, Tokyo, Japan, Dec. 2014. (Summary) This paper details our participation in the NTCIR-11 Temporalia task including Temporal Query Intent Classification(TQIC) and Temporal Information Retrieval (TIR). In the TQIC subtask, we explore the rich temporal information in the labeled and unlabeled search queries. Semi-supervised and supervised linear classiers are learned to predict the temporal classes for each search query. In the TIR subtask, we perform temporal ranking based on the technique of learning-to-rank. Two classes of features are investigated for estimating the document relevance.
206.	Haitao Yu and Fuji Ren : TUTA1 at the NTCIR-11 IMine Task, The 11th NTCIR Conference, 41-48, Tokyo, Japan, Dec. 2014. (Summary) In this paper, we detail our participation in two subtasks: subtopic mining and document ranking of the NTCIR-11 IMine task. In the subtopic mining subtask, to discover the latent hierarchy among query-like strings, our key idea is to structurally parse query-like strings by characterizing pairwise dependency in the bag-of-units perspective. Then the clustering algorithm (i.e., affinity propagation) and the Sainte-Laguë algorithm are used to obtain the target list that represents a two-level hierarchy of subtopics. In the document ranking subtask, we deploy the newly proposed 0-1 MSKP model for diversied document ranking against unclear topics. A subset of documents are optimally chosen like lling up multiple subtopic knapsacks.
207.	Changqin Quan, Bin Zhang, Fuji Ren, and : Joined cepstral distance features two-stage multi-class classification for emotional speech, Cloud Computing and Intelligence Systems (CCIS), 2014 IEEE 3rd International Conference on, 91-96, Nov. 2014. (Summary) This letter presents a joined cepstral distance and voice quality feature two-stage multi-class classification with DAG-SVM for emotional speech. The Harmonic to Noise Ratio (HNR) is applied to detect the throat diseases because it can reflect characteristics of the throat. Meanwhile, these characteristics are also strong emotional basis to distinguish emotion in speech. The cepstrum and cepstral distance is able to measure differences as well, which are well used for endpoint detecting in speech signals. In this work, cepstral distance is used for measuring the similarity between frames in emotional statement and in neutral signals. The experiment shows that cepstral distance can increase the recognition rate of emotion sad, and can balance the rate of other classes of emotion except angry. Finally, aiming at the characteristics that the different emotional expression ability of these feature set is different, a two-state classification is applied to solve confusion in multi-emotion recognition. In the recognition, Chinese mandarin emotion database is used and a large training set (1134+378 utterances) ensures a powerful modeling capability for predicting emotion. (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS.2014.7175709 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/CCIS.2014.7175709 (DOI: 10.1109/CCIS.2014.7175709)
208.	Fuji Ren, Mengni Chen, Yu Gu, and : WeWatch: Bi-Screen Video Watching Experience on Smart Devices, Cloud Computing and Intelligence Systems (CCIS), 2014 IEEE 3rd International Conference on, 265-270, Nov. 2014. (Summary) The high resolution and widescreen mobile devices have tremendous applications in our daily lives. In this paper, we demonstrate a specific bi-screen video sharing application called WeWatch that a high resolution video is played across screens of two mobile devices. It helps users to enhance their watching experience on the Android system. In order to efficiently use idle mobile devices, we develop a novel algorithm to share videos with devices with different screen sizes and resolutions. Our research provides a method which automatically controls videos based on different distances between devices. The distance is determined by the empirical WiFi RSSI values obtained through the experimental studies. We have prototyped the system and conducted a real-world energy efficiency and user experience evaluations. Results show that WeWatch has negligible impact on battery lifetime while over 80% users like our application. (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS.2014.7175740 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/CCIS.2014.7175740 (DOI: 10.1109/CCIS.2014.7175740)
209.	Xiaohua Wang, Wei Huang, Chao Jin, Min Hu and Fuji Ren : Fruit recognition based on multi-feature and multi-decision, the 9th International Conference on Natural Language Processing and Knowledge Engineering, Shen Zhen, China, Nov. 2014.
210.	Haitao Yu and Fuji Ren : Search Result Diversification via Filling Up Multiple Knapsacks, Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, 609-618, Nov. 2014. (Summary) Result diversification is a topic of great value for enhancing user experience in many fields, such as web search and recommender systems. Many existing methods generate a diversified result in a sequential manner, but they work well only if the preceding choices are optimal or close to the optimal solution. Moreover, a manually tuned parameter (say,) is often required to trade off relevance and diversity. This makes it difficult to know whether the failures are caused by the optimization criterion or the setting of . In context of web search, we formulate the result diversification task as a 0-1 multiple subtopic knapsack problem (MSKP), where a subset of documents are optimally chosen like filling up multiple subtopic knapsacks. This formulation yields no trade-off parameters to be specified beforehand. Solving the 0-1 MSKP is NP-hard, we treat the optimization of 0-1 MSKP using a graphical model over latent binary variables as a maximum posterior inference problem, and tackle it with the max-sum belief propagation algorithm. To validate the effectiveness and efficiency of the proposed 0-1 MSKP model, we conduct a series of experiments on two TREC diversity collections. The experimental results show that the proposed model outperforms several state-of-the-art methods significantly, not only in terms of standard diversity metrics (-nDCG, nERRIA and subtopic recall), but also in terms of efficiency. (Link to Publication Site) ● Publication site (DOI): 10.1145/2661829.2661933 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1145/2661829.2661933 (DOI: 10.1145/2661829.2661933)
211.	Min Hu, Yaona Zheng, Fuji Ren, He Jiang and : Age estimation and gender classification of facial images based on Local Directional Pattern, Proceedings of the 3rd IEEE International Conference on Cloud Computing and Intelligence Systems(CCIS2014), 103-107, Nov. 2014. (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS.2014.7175711 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84988286081 (DOI: 10.1109/CCIS.2014.7175711, Elsevier: Scopus)
212.	Min Hu, Xiaoyin Huang, Fuji Ren, He Jiang and : Adaptive Facial expression recognition method based on MBP and HMOG feature, Proceedings of the 3rd IEEE International Conference on Cloud Computing and Intelligence Systems(CCIS2014), 108-112, Nov. 2014. (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS.2014.7175712 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84988224613 (DOI: 10.1109/CCIS.2014.7175712, Elsevier: Scopus)
213.	Xiaohua Wang, Chao Jin, Wei Liu, Min Hu and Fuji Ren : Face recognition based on adaptive weighting and fuzzy fusion with single training sample, Proceedings of the 3rd IEEE International Conference on Cloud Computing and Intelligence Systems(CCIS2014), Nov. 2014. (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS.2014.7175739 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84948458682 (DOI: 10.1109/CCIS.2014.7175739, Elsevier: Scopus)
214.	Kazuyuki Matsumoto, Fuji Ren, Qingmei Xiao, Minoru Yoshida and Kenji Kita : Emotion Predicting Method Based on Emotion State Change of Personae according to the Other's Utterance, Proceedings of the 3rd IEEE International Conference on Cloud Computing and Intelligence Systems(CCIS2014), 427-432, Nov. 2014. (Summary) It is a very difficult task to predict others emotion from dialogue flow for dialogue system or robot, however, that is a natural task for human.As the reason, because of the emotion of human changes at all times when he / she have a conversation with other people, these changes would be considered that oc-curred by responding internal emotional state to stimulus from external world .In the researches about dialogue system, most of them are superficial feature of utterance for question-answering system, thus, internal emotional state and stimulus from external world.In this paper, we focused on the scenario dialogue sentences. We annotated the various information to the corpora for helping analyze dialogue flow or human relationships and constructed the scenario emotion corpus. We discussed that the others utterances or emotions how effect to emotion changes by analyzing this cor-pora.As the method to predict the others emotion changes from self-emotion, we proposed the predicting method based on the emotion predicting weight. As the result of evaluation experiment, the effectiveness of the proposed method could be confirmed. (Keyword) emotion prediction / scenario corpus / emotion corpus (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS.2014.7175773 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84988227783 (DOI: 10.1109/CCIS.2014.7175773, Elsevier: Scopus)
215.	Yu Gu, Lianghu Quan and Fuji Ren : WiFi-Assisted Human Activity Recognition, IEEE Asia Pacific Conference on Wireless and Mobile, 60-65, Aug. 2014. (Summary) This paper investigates the indoor activity recognition issue and proposes a novel recognition framework by exploring WiFi ambient signals. The key idea is to use data mining techniques to abstract footprints of different activities on the radio signal strength (RSS) data. Our experiments show that even using a single feature and the common k-NN classifier activities such as walking, sitting and standing can be recognized with a high accuracy, i.e. 75%. To further improve the performance, a new feature has been abstracted to represent the fluctuation of sampled data and a novel algorithm named fusion algorithm has been specifically designed based on the classification tree. Experiments show that the proposed fusion algorithm significantly outperforms the k-NN classifier in terms of both the average recognition ratio (from 75% to 92.58%) and the computational complexity. Compared to previous solutions relying on either special hardware or the cooperation of tested subjects, the proposed recognition framework is a passive and device-free solution that could be integrated into any WLAN network with low overheads. (Link to Publication Site) ● Publication site (DOI): 10.1109/APWiMob.2014.6920266 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/APWiMob.2014.6920266 (DOI: 10.1109/APWiMob.2014.6920266)
216.	Xiao Sun, Jiaqi Ye and Fuji Ren : Real Time Early-stage Influenza Detection with Emotion Factors from Sina Microblog, 25th International Conference on Computational Linguistics, 80-84, Aug. 2014. (Summary) Influenza is an acute respiratory illness that occurs every year. Detection of Influenza in its earliest stage would reduce the spread of the illness. Sina microblog is a popular microbloggingservice, provides perfect sources for flu detection due to its real-time nature and largenumber of users. In this paper we investigate the real-time flu detection problem and describea Flu model with emotion factors and sematic information (em-flu model). Experimental resultsshow the robustness and effectiveness of our method and we are hopeful that it wouldhelp health organizations in identifying flu outbreak and take timely actions to control.
217.	Fuji Ren : 1.Emotional interaction and Advanced Intelligent Robot, Keynote Speaker, CRSSC-CWI-CGrC 2014,, , CRSSC-CWI-CGrC 2014, Aug. 2014.
218.	Lu Kong, Fuji Ren, Xiao Sun and Changqin Quan : Word Frequency Statistics Model for Chinese Base Noun Phrase Identification, ICIC LNAI, Vol.8599, 635-644, Aug. 2014. (Summary) The Chinese base phrase identification plays an important role in the field of natural language processing. It needs to be improved in the recognition scope and methods currently. This paper presents a method based on word frequency statistics model for Chinese base noun phrase identification: Building the noun phrase dictionary by training corpus, calculating the co-occurrence frequency and threshold of the noun phrase, and constructing word table according to the different roles of the words in the noun phrase. Unknown word processing and rule templates are added. Improve the results with error correction processing at last. Experiments on the test corpus show that the average precision and average recall rate of the base noun phrases identification in different areas are 91.28% and 93.22%. (Link to Publication Site) ● Publication site (DOI): 10.1007/978-3-319-09339-0_64 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84958526761 (DOI: 10.1007/978-3-319-09339-0_64, Elsevier: Scopus)
219.	Lijuan Wang, Changqin Quan, Yanwei Bao and Fuji Ren : Construction of a Chinese Emotion Lexicon from Ren-CECps, ICIC LNAI, Vol.8599, 625-634, Aug. 2014. (Summary) This paper presents an automatic method to build a Chinese emotion lexicon based on the emotion corpus Ren-CECps. The method includes word extraction and emotion classification. Firstly, sentences are parsed to extract candidate emotional words. By making use of the words co-occurrence in the corpus, we get the similarity between words. And then Support Vector Machine (SVM) is adopted to classify the candidate emotional words. Experiment on the manual labeled words has shown that our classification method achieved high precision. Finally we apply our method on unlabeled corpus to get emotional words.
220.	Yanwei Bao, Changqin Quan, Lijuan Wang and Fuji Ren : The Role of Pre-processing in Twitter Sentiment Analysis, ICIC LNAI, Vol.8599, 615-624, Aug. 2014. (Summary) Recently, increasing attention has been attracted to Social Networking Sentiment Analysis. Twitter as one of the most fashional social networking platforms has been researched as a hot topic in this domain. Normally, sentiment analysis is regarded as a classification problem. Training a classifier with tweets data, there is a large amount of noise due to tweets shortness, marks, irregular words etc. In this work we explore the impact pre-processing methods make on twitter sentiment classification. We evaluate the effects of URLs, negation, repeated letters, stemming and lemmatization. Experimental results on the Stanford Twitter Sentiment Dataset show that sentiment classification accuracy rises when URLs features reservation, negation transformation and repeated letters normalization are employed while descends when stemming and lemmatization are applied. Moreover, we get a better result by augmenting the original feature space with bigram and emotions features. Comprehensive application of these measures makes us achieve classification accuracy of 85.5%.
221.	Xiao Sun, Jiaqi Ye and Fuji Ren : Multi-strategy based Sina Microblog Data Acquisition for Opinion Mining, ICIC LNAI, Vol.8599, 551-560, Aug. 2014. (Summary) As an important media for social interactions and information dissemination through the internet, Sina microblog contains emotional state and important opinion of participants. Dealing with microblog data belongs to big data areas, the premise of which is to obtain a large amount of microblog data for further analysis and data mining. For commercial interests as well as security considerations, the access to the data is becoming increasingly difficult and the API Sina microblog officially provided doesnt support large amount of data mining. In this paper, we try to design a platform that is mainly based on the access mechanism of multi-strategy and existing resources to collect data stably from Sina microblog. The results demonstrate that a combination of API and web crawler allows efficient data mining. In such way, sentiment analysis and opinion mining are performed on the data obtained by the multi-strategy method, which proved that the proposed solutions will be allowed to build straightforward application of hot words searching, opinion mining and sentiment analysis.
222.	Fuji Ren : Affective Computing and Emotional Robot, Florida State University, Florida State University,Tallahassee, USA, Jul. 2014.
223.	Fuji Ren : Mental Health Sensing and Computing Based on Affective Interaction,, Harvard University(Medical School), Boston, USA, Jul. 2014.
224.	Tian Chen, Bingdong Yang, Wei Wang, Birong Hao, Fuji Ren, Jun Liu and Yixin Wang : A test data compression scheme based on position information coding, Computing, Communication and Networking Technologies (ICCCNT), 2014 International Conference on, Hefei, China, Jul. 2014. (Summary) Under the condition of Built-off Self-test (BOST), a novel test data compression scheme based on position information coding is presented, which is targeting test data and test power consumption. The proposed scheme gets the next test stimuli by reversing some bits of the responses corresponding to the previous test vectors. During the process of bit flip, test power problem should be taken into account; both the shift power and capture power during the test should be limited in the scope of security. For shift power, need to modify the scan chain by adding blocking logic; and the capture power reduction through the test cube filling based on the response. Experimental results justify the efficacy of the proposed method in attaining test-data compression; the average compression ratio is 73.63% on the premise of capture power consumption reduced by 20%. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICCCNT.2014.6963038 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84915822698 (DOI: 10.1109/ICCCNT.2014.6963038, Elsevier: Scopus)
225.	Wei Wang, Runfeng Li, Fang Fang, Tian Chen, Fuji Ren, Jun Liu and Xi Wu : Design and realization of 3D NOC multicast router base on multicast rotational routing arithmetic, IEEE The Fifth International Conference on Computing, Communications and Networking Technologies (ICCCNT), 1-6, Hefei, Jul. 2014. (Summary) Traditional 3D NoC router may encounter the situations of congestion and hot spot. And it also doesn't have the function of multicast. In this paper, we present a new routing arithmetic called Multicast Rotational Routing Arithmetic (MRRA). It can handle several destination addresses at the same time, recombine packets, sent the same data to the different destination nodes, and avoid the congestion. The proposed algorithm is implemented by the new multicast 3D NoC router which is also proposed in this paper. The 3D NoC router is designed in Verilog HDL, simulated by Modelsim, synthesized and prototyped by Synplify and FPGA respectively. The experiment results show that the multicast router of MRRA can achieve a very good performance in terms of throughput and delay. The increased area utilization also can be tolerated. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICCCNT.2014.6963010 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/ICCCNT.2014.6963010 (DOI: 10.1109/ICCCNT.2014.6963010)
226.	Jun Liu, Qingqing Qian, Xi Wu, Fuji Ren, Wei Wang and Tian Chen : Test wrapper optimization technique using BDF and GA for 3D IP cores, IEEE The Fifth International Conference on Computing, Communications and Networking Technologies (ICCCNT), 1-6, Hefei, Jul. 2014. (Summary) To reduce pre-bond and post-bond test cost for 3D IP (Three Dimensional Intellectual Property) cores, this paper proposed a test wrapper optimization technique using BFD(Best Fit Decreasing) and GA (Genetic Algorithm) algorithm under the constraints of TSVs(Through Silicon Vias) number, the proposed technique firstly used BFD to balance the length of pre-bond wrapper chains to reduce pre-bond test time. Then, on the basis of optimization results of pre-bond wrapper chains, the GA was used to stitch pre-bond wrapper chains to form balanced post-bond wrapper chains under the constrained TSVs number to reduce hardware overhead and post-bond test time. Experimental results demonstrated the presented methodology can effectively reduce hardware overhead at the cost of little increased test time. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICCCNT.2014.6963012 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/ICCCNT.2014.6963012 (DOI: 10.1109/ICCCNT.2014.6963012)
227.	Tian Chen, Liuyang Zheng, Wei Wang, Fuji Ren, Xishan Zhang and Hao Chang : A low power BIST scheme based on block encoding, IEEE The Fifth International Conference on Computing, Communications and Networking Technologies (ICCCNT), 1-7, Hefei, Jul. 2014. (Summary) With the development of integrated circuit manufacturing technology, low power test has become a focus of concern during testing fields. This paper proposes a new low power BIST (built-in self test) scheme based on block encoding which first exploit a block re-encoding method to optimize the test cube, and then a low power test based on LFSR (linear feedback shift register) reseeding is applied. According to the compatibility of flag, the scheme proposes a grouping algorithm based on flag to divide and reorder the test cubes in the test cube set. Experimental results show that the scheme not only obtain better test compression ratio and test data storage, but also reduce the test power consumption effectively. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICCCNT.2014.6963020 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/ICCCNT.2014.6963020 (DOI: 10.1109/ICCCNT.2014.6963020)
228.	Tian Chen, Kai Liu, Xin Yi, Dandan Shen, Wei Wang, Fuji Ren and Jun Liu : A connected component-based distributed method for overlapping community detection, IEEE The Fifth International Conference on Computing, Communications and Networking Technologies (ICCCNT), 1-7, Hefei, Jul. 2014. (Summary) In order to find the overlapping community structure more quickly and accurately in complex network, this paper proposes a Connected Component-Based Distributed method (CCBD) for overlapping community detection. CCBD first divides edges set in the network into smaller one. Next, it seeks out connected component using distributed platforms and gives a serials number to them according to certain rules. Then, it classifies these connected components according to the serials number. Task nodes determine whether any two connected components and non-propagating edges can be connected to become a larger community. Finally, CCBD negotiates a new serials name for the new community. Through repeated iterations, we get the community structure in the network. Nodes belong to multiple communities are overlapping nodes. Experiment results show that CCBD has higher time efficiency benefiting from distributed computing. Moreover, the quality of communities detected by CCBD surpasses those found by other algorithms. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICCCNT.2014.6963032 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/ICCCNT.2014.6963032 (DOI: 10.1109/ICCCNT.2014.6963032)
229.	Haitao Yu and Fuji Ren : Subtopic Mining via Modifier Graph Clustering, Lecture Notes in Computer Science, Vol.8443, 337-347, Tainan,Taiwan, May 2014. (Summary) Understanding the information need encoded in a user query has long been regarded as a crucial step of effective information retrieval. In this paper, we focus on subtopic mining that aims at generating a ranked list of subtopic strings for a given topic. We propose the modifier graph based approach, under which the problem of subtopic mining reduces to that of graph clustering over the modifier graph. Compared with the existing methods, the experimental results show that our modifier-graph based approaches are robust to the sparseness problem. In particular, our approaches that perform subtopic mining at a fine-grained term-level outperform the baseline methods that perform subtopic mining at a whole query-level in terms of I-rec, D-nDCG and D#-nDCG. (Link to Publication Site) ● Publication site (DOI): 10.1007/978-3-319-06608-0_28 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84901247940 (DOI: 10.1007/978-3-319-06608-0_28, Elsevier: Scopus)
230.	Changqin Quan and Fuji Ren : Gene disease association extraction by text mining and network analysis, Proceedings of the Fifth International Workshop on Health Text Mining and Information Analysis (Loudi), 54-63, Gothenburg, Sweden, Apr. 2014. (Summary) Biomedical relations play an important role in biological processes. In this work, we combine information filtering, grammar parsing and network analysis for gene-disease association extraction. The proposed method first extracts sentences potentially containing information about gene-diseases interactions based on maximum entropy classifier with topic features. And then Probabilistic ContextFree Grammars is applied for gene-disease association extraction. The network of genes and the disease is constituted by the extracted interactions, network centrality metrics are used for calculating the importance of each gene. We used breast cancer as testing diseasefor system evaluation. The 31 top ranked genes and diseases by the weighted degree, betweenness, and closeness centralities have been checked relevance with breast cancer through NCBI database. The evaluation showed 83.9% accuracy for the testing genes and diseases, 74.2% accuracy for the testing genes.
231.	Lei Wang, Fuji Ren and Duoqian Miao : A Novel Method for Recognizing Emotions of Weblog Sentences, proceedings of IEEE/SICE SII2013 The Sixth Symposium on System Integration, 358-363, Kobe, Japan, Dec. 2013. (Summary) With plenty of online resources constantly increasing (like weblog, product reviews, news reviews, etc.), it is difficult to read them and obtain the useful information, especially emotion information. The emotion analysis on internet online information has received much attention from natural language processing field in recent years. In most existing works, single-label emotion analysis have been studied by many scientists, it often ignores the complexity of human feelings. This paper is dedicated to construct the multi-label emotion topic model for recognizing the complicated emotions of weblog sentences based on Chinese emotion corpus Ren-CECps. We employ latent topic variables and emotion variables to find complex emotions of the sentence. The results of experiments indicate that the model is reasonable and effective in recognizing the mixed emotions of weblog sentences. (Link to Publication Site) ● Publication site (DOI): 10.1109/SII.2013.6776631 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84902511791 (DOI: 10.1109/SII.2013.6776631, Elsevier: Scopus)
232.	Yao Qian, Fuji Ren and Changqin Quan : A New Preprocessing Algorithm and Local Binary Pattern Based Facial Expression Recognition, proceedings of IEEE/SICE SII2013 The Sixth Symposium on System Integration, 239-244, Kobe, Japan, Dec. 2013. (Summary) This paper presents a new preprocessing algorithm with local binary pattern for facial expression recognition. Firstly, we establish the skin color model to extract the face region, and then we use the cumulative projection to obtain the completely face region. Secondly, we rotate the inclined faces, normalize all the images, and remove the effect of light to get the required experimental samples. Finally, we use rotation invariance uniform local binary pattern operator to get the facial expression features, and then the support vector machine classifier is used for expression classification. The algorithm is implemented with Matlab and experimented on Indian male facial expression database. The proposed method obtained an accuracy of 72.75% which shows the effectiveness of the proposed algorithm. (Link to Publication Site) ● Publication site (DOI): 10.1109/SII.2013.6776757 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84902440370 (DOI: 10.1109/SII.2013.6776757, Elsevier: Scopus)
233.	Ning Liu, Fuji Ren, Xiao Sun and Changqin Quan : Microblogging Hot Events Emotion Analysis Based on Ren-CECps, proceedings of IEEE/SICE SII2013 The Sixth Symposium on System Integration, 233-238, Kobe, Japan, Dec. 2013. (Summary) Since Sina microblogging was first launched in August 2009, that seems to have become the major social media communication platform in China, microblogging is increasingly deep into life. In this study, we analyze the sentiment of microbloging hot events based on Ren-CECps. According to hot events in chronological, choosing the microblogging hot events of Beijing Heavy Fog and Xi Jinping, Peng Liyuan Visit for instance, crawling through sina microblogging we can get the corpus that contains the specified events. The method uses word frequency statistics for access microblogging corpus, analyzing trends in specific keywords concerns. At the same time, according to specific keywords related to micro-Bo, we can calculate the emotions of related microblogging via Ren-CECps. Finally, according to changes from time to time, we make a corresponding data charts, visual display of such trends. In this study, we illustrate that we can get a good result of emotion analysis using Ren-CECps in such a microblogging Chinese text with fragmentation and discrete feature. As a further indication of such excellent Chinese emotion corpus, the practical and research value in it are enormous. (Link to Publication Site) ● Publication site (DOI): 10.1109/SII.2013.6776683 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84902471502 (DOI: 10.1109/SII.2013.6776683, Elsevier: Scopus)
234.	Xiaohua Wang, Chao Jin, Wei Liu, Min Hu, Liangfeng Xu and Fuji Ren : Feature Fusion of HOG and WLD for Facial Expression Recognition, proceedings of IEEE/SICE SII2013 The Sixth Symposium on System Integration, 227-232, Kobe, Japan, Dec. 2013. (Summary) A considerable amount of research work has beendone for facial expression recognition using local or globalfeature extraction methods. Weber Local Descriptor (WLD), asimple and robust local image descriptor, is recently developedfor local feature extraction. In facial expression recognition, theinformation contained in the local is important for therecognition result. The Histograms of Oriented Gradients(HOG) can well describe the local area information usinggradient and orientation density distribution of the edge. Inorder to solve the lack of contour and shape information only byWLD features and to extract facial local features moreefficiently, we propose a hybrid approach that combines theWLD with HOG features. We divide the images into blocks andweight each of them, then extract the two features and fuse them.At last, the weighted fused histograms are used to classify facialexpressions by chi-square distance and the nearest neighbormethod. The proposed method is applied on popular JAFFEand Cohn-Kanade facial expression databases and recognitionrate is up to 93.97% and 95.86%. Compared with the GaborWavelet, LBP, and AAM and experimental results show that theproposed method achieves better performance for facialexpression recognition. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84902479323 (Elsevier: Scopus)
235.	Changqin Quan, Dongyu Wan, Bin Zhang and Fuji Ren : Reduce the Dimensions of Emotional Features by Principal Component Analysis for Speech Emotion Recognition, proceedings of IEEE/SICE SII2013 The Sixth Symposium on System Integration, 222-226, Kobe, Japan, Dec. 2013. (Summary) In this paper, the principal component analysis (PCA) is applied to speech emotion recognition for improving the accuracy of the system. The traditional prosodic features like pitch-related features and formant-related features are extracted from the Berlin speech database [7] and a Chinese database. These collected feature data is processed by PCA to remove the irrelevant information. After that, three kinds of features including the processed features by PCA, unprocessed features and other speech-related features are used to train a SVM classifier. And six emotions are tested in the experiment. The classification accuracy of the processed features by PCA is about 3.1% higher than the unprocessed features and about 17.6% higher than the MFCC features when using 240 utterances. The recognition accuracies among different emotions in both databases are also presented in the study. (Link to Publication Site) ● Publication site (DOI): 10.1109/SII.2013.6776653 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84902455517 (DOI: 10.1109/SII.2013.6776653, Elsevier: Scopus)
236.	Changqin Quan, Xiquan Wei and Fuji Ren : Combine Sentiment Lexicon and Dependency Parsing for Sentiment Classification, proceedings of IEEE/SICE SII2013 The Sixth Symposium on System Integration, 100-104, Kobe, Japan, Dec. 2013. (Summary) With the rapid development of internet technology and e-commerce sites, there are more and more products review in the network. People are willing to make a survey on the internet before purchasing the products. The automatic identification of the sentiment of comments is necessary. We propose a method, which combines sentiment lexicon and dependency parsing to determine the sentiment orientation and the positive or negative attitudes of the topic. The dependency parsing is used to get the objects and sentiment words. Then the allocation of weights is done, and finally the positive and negative results of the products evaluation are concluded. Experiments show that the validity and efficiency of the proposed method. (Link to Publication Site) ● Publication site (DOI): 10.1109/SII.2013.6776652 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84902479906 (DOI: 10.1109/SII.2013.6776652, Elsevier: Scopus)
237.	Zhong Huang and Fuji Ren : Facial Expression Recognition Based on Active Appearance Model & Scale-Invariant Feature Transform, proceedings of IEEE/SICE SII2013 The Sixth Symposium on System Integration, 94-99, Kobe, Japan, Dec. 2013. (Summary) The active appearance model (AAM), one of the most effective facial feature localization methods, is widely used in facial expression recognition. However, the results of this model with non-frontal face are not ideal. Thus, we propose a new method for facial expression recognition based on AAM and scale-invariant feature transform (SIFT). The proposed method uses AAM to locate the feature points of a facial expression image. SIFT descriptors are then utilized to describe these feature points, and the gradient direction histogram of the pixels surrounding these points are used to form point feature vectors. The chi-square distance and the nearest neighbor classifier is applied to accomplish the facial expression recognition task. The experimental results from standard expression databases and multi-posture expressions show that the proposed method not only improves the recognition rates of the frontal face but also has better robustness for non-frontal facial expressions under some deflection angles. (Link to Publication Site) ● Publication site (DOI): 10.1109/SII.2013.6776620 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84902517301 (DOI: 10.1109/SII.2013.6776620, Elsevier: Scopus)
238.	Rui Li, Zhuguo Yu, Min Hu, Zhong Huang and Fuji Ren : Facial Expression Recognition Algorithm Based on Feature Fusion Adaptive Weighted HLAC, proceedings of IEEE/SICE SII2013 The Sixth Symposium on System Integration, 88-93, Kobe, Japan, Dec. 2013. (Summary) In this paper, a novel method of facial expression recognition based on adaptive weighted higher-order local autocorrelation coefficient (WHLAC) is presented. Firstly, The method gets whole face region and sub-regions of eyebrows, eyes, nose and mouth. Secondly, the global features of the face regions and local features of the sub-regions are extracted by HLAC, the weights of sub-regions are calculated by fisher linear discriminant (FLD), and then these two parts features are fused together by the weights. Finally, the fused features are classified by FLD. The experimental results show that the proposed method has higher recognition rate and lower computational cost than Gabor, WLBP, HLAC for facial expression recognition. (Link to Publication Site) ● Publication site (DOI): 10.1109/SII.2013.6776616 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84902530447 (DOI: 10.1109/SII.2013.6776616, Elsevier: Scopus)
239.	He Jiang, Min Hu, Hongbo Chen, Kun Li, Xiaohua Wang and Fuji Ren : Facial Expression Recognition Based on Multi-Scale Vector Triangle, proceedings of IEEE/SICE SII2013 The Sixth Symposium on System Integration, 82-87, Kobe, Japan, Dec. 2013. (Summary) Image description is not sufficient in traditional facial expression recognition (FER) methods, therefore this paper proposes a FER method based on multi-scale vector triangle. It combines vector triangle pattern with image pyramid to extract facial expression features. Firstly, construct a facial image pyramid to produce images in different scales. Secondly, divide each image into blocks, and extract vector triangle features of each sub-image. Then, use histogram to statistical characteristics, and calculate Euclidean distance between the histograms. Finally, fusion weighted eigenvalues and come to the recognition results. Multi-scale vector triangle pattern can not only avoid the loss of information in image asymmetric regions, but also reflect image features in different scales. It can describe images more adequately. In order to verify the effectiveness of the algorithm, this paper uses the Japanese Female Facial Expression (JAFFE) database to do the experiments and compare the results with Complete Local Binary Patterns (CLBP), Gabor wavelet, Active Appearance Models (AAM) and so on. Experimental results indicate that this method has higher recognition rate and better real-time effect. (Link to Publication Site) ● Publication site (DOI): 10.1109/SII.2013.6776615 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84902525890 (DOI: 10.1109/SII.2013.6776615, Elsevier: Scopus)
240.	Xiao Sun, Chengcheng Li, Chenyi Tang and Fuji Ren : Mining Semantic Orientation of Multiword Expression from Chinese Microblogging with Discriminative Latent Model, 2013 International Conference on Asian Language Processing, 117-120, Urumqi, China, Aug. 2013. (Summary) Extracting semantic orientation of Multiword Expression, especially some newly generated Multiword Expression from internet, is an important task for sentiment analysis of web texts or other real word text as some Multiword Expressions can express more integrative sentiments than words units. This paper proposes a method contains a novel latent discriminative algorithm, which attempts to attack this problem by integrating discriminative model and latent value model. Although Chinese Multiword Expressions consist of multiple words, the semantic orientation of the Multiword Expression is not just simple integration of orientations of the component words, as some words can invert the affective orientation so the Multiword Expressions can have totally opposite semantic orientation. In order to capture the property of such Multiword Expressions, hidden semi-CRF which includes a latent valuable layer, which can be used to address dual-sequence labeling tasks synchronously, is adopted. The method is tested experimentally by adopting a manually labeled set of positive and negative Multiword Expressions from microblog or other internet resources, and the experiments have shown very promising results, which is comparable to the best value ever reported. (Link to Publication Site) ● Publication site (DOI): 10.1109/IALP.2013.41 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/IALP.2013.41 (DOI: 10.1109/IALP.2013.41)
241.	Qingli Zhang, Ning An, Kunxia Wang, Fuji Ren and Lian Li : Speech emotion recognition using combination of features, Fourth International Conference on Intelligent Control and Information Processing, 523-528, Beijing, China, Jun. 2013. (Summary) In this paper, we study how speech features' numbers and statistical values impact recognition accuracy of emotions present in speech. With Gaussian Mixture Model (GMM), we identify two effective features, namely Mel Frequency Cepstrum Coefficients (MFCCs) and Auto Correlation Function Coefficients (ACFC) extracted directly from speech signal. Using GMM supervector formed by values of MFCCs, delta MFCCs and ACFC, we conduct experiments with Berlin emotional database considering six previously proposed emotions: anger, disgust, fear, happy, neutral and sad. Our method achieve emotion recognition rate of 74.45%, significantly better than 59.00% achieved previously. To prove the broad applicability of our method, we also conduct experiments considering a different set of emotions: anger, boredom, fear, happy, neutral and sad. Our emotion recognition rate of 75.00% is again better than71.00% of the method of hidden Markov model with MFCC, delta MFCC, cepstral coefficient and speech energy. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICICIP.2013.6568131 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/ICICIP.2013.6568131 (DOI: 10.1109/ICICIP.2013.6568131)
242.	Yu Gu, Yusheng Ji, Fuji Ren and Ji Li : Network lifetime optimization in wireless healthcare systems: Understanding the gap between online and offline scenarios, proceedings of Communications, 1774-1778, Budapest, Hungary, Jun. 2013. (Summary) In this paper, we study the network Lifetime Maximization problem in Mobile healthcare sensor systems (LMM). For the healthecare system, we consider a dynamic scenario where users are mobile at their own wills and periodically report their personal health information (PHI) to a static sink, e.g. a powerful server, for further processing and distributing. The objective is to optimize the network lifetime by flow scheduling. The major difficulty lies in the time-dependent network topologies. Therefore, we propose a novel temporal-spatial network modeling method by extending current model with time dimension. Based on this model, we show that if the movement of users are known in advance (i.e. offline case), the problem can be optimally solved in polynomial time by a linear programming. However, the online LMM problem is much more difficult to tackle, since we prove that there exists no online algorithm with a constant performance ratio to the offline optimal algorithm in terms of the network lifetime. We further design simulations to show the performance gap between online and offline LMM. Considering the user mobility within a given scenario follows some certain patterns, we show the potential improvements of using a prediction-based method. This investigation provides certain insights on designing efficient online algorithms for the LMM problem. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICC.2013.6654776 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/ICC.2013.6654776 (DOI: 10.1109/ICC.2013.6654776)
243.	Kazuyuki Matsumoto, Kenji Kita and Fuji Ren : Emotion Estimation from Sentence Using Relation between Japanese Slangs and Emotion Expressions, Proceedings of 26th Pacific Asia Conference on Language,Information and Computation, 377-384, Nov. 2012. (Summary) Most of Japanese slang words such as Wakamono Kotoba are analyzed as unknown word or segmented wrongly by the morphological analysis system. These problems are causing negative effect on sentiment analysis in text. These words generally have many varieties of notations and conjugations, and they lack versatility. As a result, many of them are not registered in the dictionaries, making morphological analysis more difficult. In this paper, we aimed to decrease such negative effects of Wakamono Kotoba for the accuracy of emotion estimation from sentence and proposed a method to increase the accuracy by using a classification method based on machine learning. In this method we used emotional expressions which had high relevance with Wakamono Kotoba as feature. As a result, the proposed method obtained 20% higher accuracy than the method only using morpheme Ngram as feature. (Keyword) Emotion Corpus / Japanese Slang / Out of Vocabulary
244.	Sohrab Golam Mohammad and Fuji Ren : CLASS-INDEXING: THE EFFECTIVENESS OF CLASSS-PACE-DENSITY IN HIGH AND LOW-DIMENSIONAL VECTOR SPACE FOR TEXT CLASSIFICATION, IEEE International Conference on Cloud Computing and Intelligence Systems, 2034-2042, Hangzhou, China, Oct. 2012. (Summary) Most of the previous studies of termweighting schemes emphasize on the documentindexing-based term weighting approach to addressautomatic text classification (ATC). In this study, weintroduce class-indexing-based term-weightingapproaches and judge their effects in high andcomparatively low-dimensional dataset over the TF.IDFapproach. First, we implement a class-indexing-basedTF.IDF.ICF term weighting approach in which theinverse class frequency (ICF) is incorporated; providepositive discrimination on rare terms and biased againstfrequent terms in the TC task. Therefore, we revised theICF function and implemented a new inverse class spacedensity frequency (ICSF) multiplied by TF.IDF, andgenerated the TF.IDF.ICSF that provides a positivediscrimination on infrequent and frequent terms. Wepresent detailed evaluation of each category for theReuters-21578 and 20 Newsgroups datasets. Theexperiment results show that the proposed classindexing-based TF.IDF.ICSF term weighting approachplays a significant role to overcome the problem ofdimensionality reduction in the feature space. (Keyword) Text classification / indexing / term weighting / machine learning / centroid classifier
245.	Song Liu and Fuji Ren : RELATION EXTRACTION FROM WIKIPEDIA ARTICLES BY ENTITIES CLUSTERING, IEEE International Conference on Cloud Computing and Intelligence Systems, 1491-1495, Hangzhou, China, Oct. 2012. (Summary) Wikipedia is an encyclopedia based on wikitechnology. It is multilingual high quality knowledgebase. In this work a episode based extraction method areproposed to extract relations from Wikipedia articles.The entities are clustered and labeled. The relationextraction is benefited by the information redundancyprovided by the clusters. A strict Wikipedia entitiesclustering algorithm based on the category system andfirst sentence of the article is approached. This workrequired less manual assist. And the relations areabundant. The results are comparable with other works. (Keyword) Relation extraction / Entities clustering / Episode (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS.2012.6664633 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84890358249 (DOI: 10.1109/CCIS.2012.6664633, Elsevier: Scopus)
246.	Haitao Yu and Fuji Ren : Role-explicit Query Identification and Intent Role Annotation, The 21st ACM International Conference on Information and Knowledge Management, 1163-1172, Maui, HI, USA, Oct. 2012. (Summary) Understanding the information need or intent encoded within a query has long been regarded as an essential factor of effective information retrieval. For better query representation and understanding, two intent roles (kernel-object and modifier) are introduced to structurally parse a class of role-explicit queries, which constitute a majority of common user queries. Furthermore, we focus on two research problems: RP-1: Given a role-explicit query, how to identify the kernel-object and modifier, namely intent role annotation; RP-2: How to determine whether an arbitrary query is role-explicit or not. To solve RP-1, we propose a simplified word n-gram role model (SWNR), which quantifies the generating probability of a role-explicit query and performs intent role annotation effectively. Using a set of discriminative features, we build classifiers to address RP-2 in a supervised manner. The experimental results show that: (1) SWNR can achieve a satisfactory performance, more than 73% in terms of different metrics; (2) The classifiers can achieve more than 90% precision in identifying role-explicit queries; (3) Compared with traditional techniques for query representation and understanding, e.g., name entity recognition in query and class-level query intent inference, intent role annotation provides a more flexible framework and a number of applications can benefit from annotating role-explicit queries, such as intent mining and diversified document ranking.
247.	Yan Sun, Fuji Ren, Xin Kang and Changqin Quan : A Japanese Adverb Emotion Corpus for Japanese Emotion Analysis, 8th International Conference on Natural Language Processing and Knowledge Engineering, 418-423, Hefei, China, Sep. 2012. (Summary) Computing emotions from text has become a popular direction in natural language processing. The words are extensively studied as features to predict emotions in previous works, but very few studies have distinguished words with particular part of speech features in this task. In Japanese adverbs which are frequently used in both written and spoken language, have been observed to remarkably impact the sentence emotions. In this paper, we focus on such impacts of adverbs among sentences, and develop a Japanese adverb-emotion corpus with totally 3864 Japanese sentences. Adverb features are extracted from sentences, and new adverb categories, an adverb-emotion lexicon, as well as adverb-emotion rules are summarized according to the different functions of these adverbs in text emotion expressions. The developed Japanese adverb-emotion corpus lays a foundation for further Japanese emotion analysis and recognition in text. (Keyword) Japanese Adverb / Emotion Prediction / Corpus / Features
248.	Yu Wang, Lian Li, Fuji Ren and Changqin Quan : POMDP Based Affective Model and It's Application on An Intelligent Music Player, 8th International Conference on Natural Language Processing and Knowledge Engineering, 407-417, Hefei, China, Sep. 2012. (Summary) Partially Observable Markov Decision Processes (POMDP) model has been confirmed to be appropriate for spoken dialogue system. Based on this model, we construct a new factored POMDP model to describe the emotional dialogue system. First we divide the users state into users goal (or intention) and user's emotion. In order to respond effectively to the users state, we divide the agents action into emotional coping and goal response accordingly. Then we construct the observation model, the users goal model, and the users emotion model respectively. Finally, the model is proved to be valid by an example of an intelligent music player. (Keyword) POMDP model / affective computing / dialogue system
249.	Song Liu and Fuji Ren : How to and Why Question Answering using Syntactic Semantic and Pragmatic Features, 8th International Conference on Natural Language Processing and Knowledge Engineering, 216-226, Hefei, China, Sep. 2012. (Summary) Question answering system assists people to acquire the valuable information in a natural way. "Why" and "how to" questions express two kinds of essential information requirements. The two kinds of complex questions that need more information to find the answers. In this paper, syntactic, semantic and pragmatic features are employed to find answers for "why" and "how to" questions. And ranking learning approaches are applied to re-rank the candidate answers. And wrappers strategy are used to select the optimized features combination. The results show that answers are improved by using the combination of syntactic, semantic and pragmatic features. (Keyword) question answering / syntactic / semantic / pragmatic / ranking learning
250.	Changqin Quan, Xiao Sun and Fuji Ren : Feature Based Review Classification for Fine-grained Sentiment Analysis, 8th International Conference on Natural Language Processing and Knowledge Engineering, 106-116, Hefei, China, Sep. 2012. (Summary) The researches on subjectivity, opinions or sentiments, named sentiment analysis, have a great deal of applications in E-business, opinion polls and many other fields. Feature-based sentiment classification can provide more fine grained sentiment analysis. In the problem of feature-level sentiment classification, identifying implicit review features is a big challenge. In this paper, we propose a new measure of PMI-TFIDF by combining PMI (Point wise mutual information) and TF-IDF (term frequencyinverse document frequency) to measure the association of words for extending related features. By adding the importance measure of a word to documents, PMI-TFIDF can provide more effective distinction between words than PMI. Based on PMI-TFIDF, the related words with high relevance for a feature can be obtained. Kernel methods (KMs) are state-of-the-art for solving machine learning problems. Based on the measure of PMI-TFIDF, we applied Polynomial Kernel (PK) method to get the similarities between a review and the related word lists of different features for feature based review classification. The best experimental results on feature based book reviews classification achieved the precision of 82.5%. (Keyword) Sentiment Analysis / feature / PMI-TFIDF / Polynomial Kernel
251.	Xiao Sun, Changqin Quan and Fuji Ren : Semantic Orientation Extraction of Chinese Phrases by Discriminative Model and Global Features, 8th International Conference on Natural Language Processing and Knowledge Engineering, 64-74, Hefei, China, Sep. 2012. (Summary) Extracting semantic orientation of phrases, especially some newly generated phrases frominternet, is an important task for sentiment analysis of web texts or other real word textas some phrases can express more integrative sentiments than words units. This paperproposes a method contains a novel latent discriminative algorithm, which attempts toattack this problem by integrating discriminative model and latent value model. AlthoughChinese phrases consist of multiple words, the semantic orientation of the phrase is notjust simple integration of orientations of the component words, as some words can invertthe aective orientation so the phrases can have totally opposite semantic orientation. Inorder to capture the property of such phrases, hidden semi-CRF which includes a latentvaluable layer, which can be used to address dual-sequence labeling tasks synchronously,is adopted. The method is tested experimentally by adopting a manually labeled setof positive and negative phrases from microblog or other internet resources, and theexperiments have shown very promising results, which is comparable to the best valueever reported. (Keyword) Semantic Orientation Extraction / Chinese Phrases / Discriminative Latent Model / Global Features
252.	Kazuyuki Matsumoto, Yoshioka Nobuhiro, Kenji Kita and Fuji Ren : Judgment of Depressive Tendency from Emotional Fluctuation in Weblog, Proceedings of the 16th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems - KES2012, 545-554, Sep. 2012. (Summary) Some people who have tendency toward depression describe their inner thoughts vividly in their weblogs. Such descriptions are sometimes made consciously but at other times unconsciously by the authors. If such unconscious authors could become aware of their own symptom of the depression, that would contribute to early detection and treatment of the sickness. To achieve this, it is essential to find out the tendency of depression from the descriptions in weblog. Because the symptom of depression is not static, we attempted to detect the tendency of depression focusing on the temporal fluctuation of emotion of the authors. As many weblogs describe what happened or what the authors felt in daily life like a personal journal, we thought that weblogs were ideal for obtaining the time-varying emotion of the authors. In this paper, we proposed the method to detect the tendency of depression in weblog. Our method is based on the temporal fluctuation of emotion described by the authors. (Keyword) Weblog / Emotional Fluctuation / Depressive Tendency
253.	Yimin Tang, Fuji Ren and Yanxiang Chen : Universal triple I method and its application to textual emotion polarity recognition, World Scientific Proceedings Series on Computer Engineering and Information Science 5, 189-196, Xian, China, May 2012.
254.	Peilin Jiang, Fei Wang, Fuji Ren and Nanning Zheng : Emotion Ontology Construction from Chinese Knowledge, Computational Linguistics and Intelligent Text Processing, Vol.LNCS7181, 603-614, New Delhi, India, Mar. 2012.
255.	Wu Yunong, Kenji Kita, Fuji Ren, Kazuyuki Matsumoto and Kang Xin : Exploring Emotional Words for Chinese Document Chief Emotion Analysis, Proceedings of 25th Pacific Asia Conference on Language, Information and Computation(PACLIC2011), 597-606, Dec. 2011. (Summary) In this study, we develop a document emotion analysis model by making use of the function of emotional words annotation. Eight basic emotion categories have been selected, including Expect, Joy, Love, Surprise, Anxiety, Sorrow, Anger and Hate, for both the word and the document level emotion analysis. We introduce two parameters, term relevance and term frequency, to evaluate the relations between the word emotions and the document emotions. Promising experimental results reveal the effectiveness of our document emotion analysis model under different emotion situations. (Keyword) emotional words annotation / document emotion analysis / term relevance / term frequency
256.	Yunong Wu, Kenji Kita, Fuji Ren, Kazuyuki Matsumoto and XIN KANG : Exploring Emotional Words for Chinese Document Chief Emotion Analysis, The 25th Pacific Asia Conference on Language, Information, and Computation (PACLIC25), 597-606, Dec. 2011.
257.	Wu Yunong, Kenji Kita, Fuji Ren, Kazuyuki Matsumoto and XIN KANG : Exploring Emotional Words for Chinese Document Chief Emotion Analysis, The 25th Pacific Asia Conference on Language, Information, and Computation (PACLIC25), 597-606, Dec. 2011.
258.	Shoko Fuji, Mai Date, Yuko Nagai, Yuko Yasuhara, Tetsuya Tanioka and Fuji Ren : Research on the possibility of humanoid robots to assist in medical activities in nursing homes and convalescent wards, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 459-463, Tokushima, Nov. 2011. (Summary) In Japan, increasing attention has been given to using humanoid robots to solve problems concerning personnel shortage and to reduce duty workload in clinical and nursing situations. Currently, the development of robots is not yet at the level where they can function like human medical and health care professionals. For this reason, it is imperative to discover ways in which humanoid robots can be used to solve the issues of personnel shortage and duty workload. The aim of this research is to clarify the impressions nurse and care staff has toward humanoid robots. The research focuses on 1) whether there are any duties humanoids can undertake and 2) what is required of humanoids to perform clinical functions. This research was approved by the ethical review board of University Hospital A, and a mail survey was conducted between August and September, 2010. The respondents were 939 members of nurse and care staff working in nursing homes and convalescent wards. Among the reasons given by respondents who think that humanoids cannot do any clinical duty, the most common was Not clear what and how much ability humanoids have, chosen by 70.41 percent of respondents. Regarding the qualities required of humanoid robots on the aspect of ethical considerations, 63.79 percent chose Not causing harm to humans, making it the most common response. From the above results, it appears that personnel working in nursing homes and convalescent wards do not have enough accurate information on humanoid robots. It is therefore necessary that for future engagement of humanoid robots in clinical duty, advanced and detailed information on the ability and performance of humanoid robots be disseminated, so that not only patients but also medical staff can accept them without difficulty. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2011.6138243 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84857344108 (DOI: 10.1109/NLPKE.2011.6138243, Elsevier: Scopus)
259.	Peilin Jiang, Fuji Ren, Fei Wang and nanning Zheng : Complex Emotion Categorization and Tagging for Chinese, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 334-339, Tokushima, Nov. 2011. (Summary) To understand emotion and make machine emotion is one of the goals of affective computing. In order to understand language from interface of machine, both the meaning and the emotion are necessary to be interpreted correctly. But until now the study of fine-grained theory of emotion is still full of challenges. In this paper, a novel method to analyze emotion category is proposed according to the statistics of affective word hierarchy in Dictionary of contemporary Chinese. The emotion hierarchy is called complex emotion. Firstly, over 7,000 common affective words have be annotated and their detailed explanations had been collected for an affective lexicon, then we analyze the consistent relationship in the affective lexicon and consequently 52 salient complex emotion state hierarchies are categorized and tagged by a lexical affective clustering algorithm. The complex emotions are compared to the traditional definitions of basic emotions in psychology and have been evaluated to be valid by kappa value in the experiment. Moreover we also have tagged the semantic orientation for the collected words. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2011.6138220 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84863132513 (DOI: 10.1109/NLPKE.2011.6138220, Elsevier: Scopus)
260.	Kazuyuki Matsumoto, Kenji Kita and Fuji Ren : Emotion Estimation of Wakamono Kotoba Based on Distance of Word Emotional Vector, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 214-220, Tokushima, Nov. 2011. (Summary) Recently, there are many research that aim at estimating emotion from text. The meaning of language expression that we use in daily life varies depending on the context used. In that sense, language expression conveys ambiguous information. Wakamono Kotoba are words used by young people, and they also have semantic ambiguity. Most of the Wakamono Kotoba are not registered in the existing dictionaries, making it difficult for a system to recognize the meaning of Wakamono Kotoba. In this paper, we propose a method for estimating emotion in Wakamono Kotoba that were not registered in the system, by using Wakamono Kotoba example sentences as features. The proposed method applied Earth Movers Distance to vector of words. As a result of the evaluation experiment, higher estimation accuracy was obtained by considering emotional distance between words -- an approach that had not been used in the conventional research -- than by using only word importance value. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2011.6138197 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84857271107 (DOI: 10.1109/NLPKE.2011.6138197, Elsevier: Scopus)
261.	Liping Mi, Fuji Ren and Hideo Araki : Differences of Japanese Kanji and Kana during the Memory Processing, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 205-208, Tokushima, Nov. 2011. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2011.6138195 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84857274532 (DOI: 10.1109/NLPKE.2011.6138195, Elsevier: Scopus)
262.	Changqin Quan and Fuji Ren : Selecting clause emotion for sentence emotion recognition, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 194-198, Tokushima, Nov. 2011. (Summary) Sentence emotion recognition allows for deeper analysis of textual emotion. Based on the finding that sentence emotional focus can be expressed by some clauses in this sentence, this work proposes to select clause emotion for sentence emotion recognition. In the first step, a Maximum entropy (MaxEnt) classification model has been built for word emotion recognition. In the second step, a homogeneous Markov model (HMM) classification method is used for clause emotion classification. In the third step, nine text features are selected, and genetic algorithm (GA) is used to specify the weight of each text feature. The sentence emotion is an addition of all selected clause states in this sentence. The experimental results showed that there are 9.1% and 3.6% improvement for the two tasks respectively when comparing with the baseline. It is demonstrated that clause selection is able to improve the performance of sentence emotion recognition significantly. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2011.6138193 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84857307355 (DOI: 10.1109/NLPKE.2011.6138193, Elsevier: Scopus)
263.	Xin Kang and Fuji Ren : Sampling Latent Emotions and Topics in a Hierarchical Bayesian Network, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 37-42, Tokushima, Nov. 2011. (Summary) Text emotion analysis suffers from the lack of faithful emotion features, and the difficulty of mining multiple emotions that are mixed together. In this paper, we provide a Gibbs sampling method to solve these two problems. We explicitly characterize the emotion combination phenomenons, and predict the complex emotions of words together with the emotion intensities for each singular emotion through raw texts. Both emotions and emotion intensities are embedded as latent random variables in a hierarchical Bayesian network, while only the words and some preliminary expectations are represented as observed variables. The model which we call word emotion topic (WET) model, also depicts the distribution of word emotions among different topics, which helps to study the variation of word topics and word emotions. Experiment shows promising results of word emotion prediction, which outperforms traditional parsing methods such as Hidden Markov Model and Conditional Random Fields on raw text. The result also presents interesting emotion-topic variations through blog articles. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2011.6138166 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84857327170 (DOI: 10.1109/NLPKE.2011.6138166, Elsevier: Scopus)
264.	Yiming Tang, Fuji Ren, Xiao Sun and Yanxiang Chen : Reverse universal triple I method of (1,1,2) type for the Lukasiewicz implication, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 27-29, Tokushima, Nov. 2011. (Summary) A new fuzzy reasoning method called the reverse universal triple I method of (1,1,2) type (reverse universal triple I method for short) is proposed and investigated by means of the famous Lukasiewicz implication, which contains the reverse triple I method as its special case. The reverse triple I principles are improved, and the optimal solutions of reverse universal triple I method are obtained for Fuzzy Modus Ponens (FMP) and Fuzzy Modus Tollens (FMT). Furthermore, it is found that the reverse universal triple I method has the reversibility property. Lastly, the reverse universal triple I method is further generalized to the alpha-reverse universal triple I method, and the related principles and optimal solutions are achieved. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2011.6138164 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84863146420 (DOI: 10.1109/NLPKE.2011.6138164, Elsevier: Scopus)
265.	Fuji Ren : Robotics Cloud and Robotics School, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 1-8, Tokushima, Nov. 2011. (Summary) In the near future, robots with advanced intelligence will be used for the service of society, families, and individuals. In this paper, we propose the concept of an advanced intelligence machine, which is a device that uses both natural and artificial intelligence and is capable of affective recognition and generation of affective speech and behavior. We describe the concept of a robotics cloud for use by advanced intelligence machines in human-robot interactions and provide a theoretical framework and technology blueprint of the construction of a robotics cloud. In addition, we propose a robotics school for building robotics clouds and describe a framework for the school, its certification program, and a method for authentication of the school. The influence of robots on the development of society, scientific and technological progress, and human-robot relationships are also discussed. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2011.6137767 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84857324867 (DOI: 10.1109/NLPKE.2011.6137767, Elsevier: Scopus)
266.	Yunong Wu, Kenji Kita, Fuji Ren, Kazuyuki Matsumoto and XIN KANG : Modification Relations based Emotional Keywords Annotation using Conditional Random Fields, The 4th International Conference on Intelligent Networks and Intelligent Systems (ICINIS2011), 81-88, Nov. 2011.
267.	Wu Yunong, Kenji Kita, Fuji Ren, Kazuyuki Matsumoto and XIN KANG : Modification Relations based Emotional Keywords Annotation using Conditional Random Fields, The 4th International Conference on Intelligent Networks and Intelligent Systems (ICINIS2011), 81-88, Nov. 2011.
268.	Wu Yunong, Kenji Kita, Fuji Ren, Kazuyuki Matsumoto and Kang Xin : Modification Relations Based Emotional Keywords Annotation Using Conditional Random Fields, Proceedings of 2011 Fourth International Conference on Intelligent Networks and Intelligent Systems, 81-84, Oct. 2011. (Summary) In this study, we demonstrate the effectiveness of modification features for emotional keywords annotation on Chinese sentences extracted from a Chinese emotion corpus. Eight basic word emotion categories have been selected and Conditional Random Fields is employed in eight experiments with different sets of features. Our result shows that modification features make the contribution to emotional keywords annotation. (Keyword) modification features / emotional keywords annotation / CRFs
269.	Jun Wang, Lei Li and Fuji Ren : An Improved Method of Extracting Emotional Attribute of Relations Based on Syntactical Analysis, Proc. of IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS 2011), 457-461, Beijing, Sep. 2011. (Summary) Social network plays an important role in thisnetwork age. With development of social network,people hope more attribute and more precisedescription about relation which is the key elementof network. This paper proposes an improvedmethod of extracting emotional attribute ofrelations from Chinese events based on syntacticalanalysis. In our work, we improved the defect ofprevious method that can not deal with multipleentities in one sentence. In addition, a large-scaleChinese emotional dictionary not only emotionalverbs was used in the extraction of emotionalattribute. Experiment showed our method achievedsatisfied performance. (Keyword) social network / emotional attribute / syntactical analysis (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS.2011.6045109 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-80055114337 (DOI: 10.1109/CCIS.2011.6045109, Elsevier: Scopus)
270.	Song Liu and Fuji Ren : PARAGRAPH ACT BASED PRAGMATIC INFORMATION EXTRACTION IN QUESTION ANSWERING, Proc. of IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS 2011), 153-157, Beijing, Sep. 2011. (Summary) In Question Answering System the greatesthardship is crossing the gap between the questionsand corpus to find the appropriate answers. Thequestions and corpus are in different context, tofind the answers the inference whether onecandidate sentence fits the user's request isnecessary. Pragmatic is concerned with inferenceabout the utterances and user. It is a bridge acrossthe gap of questions and corpus. In this paper weanalyze the elements of pragmatic and extract thepragmatic information from the corpus based onthe paragraph act. The pragmatic information isalso well organized. And the experiments showthat the appended pragmatic informationsignificantly improves the performance of theQuestion Answering System either the precision,recall or F score especially in the condition that thequantity of answer is restricted. (Keyword) Question Answering / pragmatic information / information extraction / paragraph act (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS.2011.6045051 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-80055102587 (DOI: 10.1109/CCIS.2011.6045051, Elsevier: Scopus)
271.	Ji Li and Fuji Ren : CREATING A CHINESE EMOTION LEXICON BASED ON CORPUS REN-CECPS, Proc. of IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS 2011), 80-84, Beijing, Sep. 2011. (Summary) As a basic emotion resource, an emotion lexiconplays a very important role in the classification andrecognition of emotion in text. This paper proposesan automatic approach to create a Chinese emotionlexicon with tag of emotion intensity based on theemotion corpus Ren-CECps 1.0. We present a newalgorithm of emotion vector computation bymaking use of two language dictionaries TongyiciCilin and HowNet. Comparing with theexperimental results on verbs by SVMclassification method, our approach is provedfeasible and effective. (Keyword) Emotion Lexicon / Emotion Intensity / Tongyici Cilin / HowNet / Semantic Similarity (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS.2011.6045036 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-80055103743 (DOI: 10.1109/CCIS.2011.6045036, Elsevier: Scopus)
272.	Jia Ma and Fuji Ren : DETECT AND TRACK THE DYNAMIC DEFORMATION HUMAN BODY WITH THE ACTIVE SHAPE MODEL MODIFIED BY MOTION VECTORS, Proc. of IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS 2011), 587-591, Beijing, Sep. 2011. (Summary) At present, many systems are being used in the detection of human body from video, especially the moving human body. These systems usually recognize the human body features, such as learning the human body features by training, recognition of the skin color or body shape, and identify the specifically movement of human body. These methods have some problems. The training methods require a lot of training data, but only identify specific targets. The methods of identify the shape of human body and skin color are a great influenced by the video quality and content. The methods of detecting motion features are often complex and greatly relied to the 3D data. In this study, we propose an Active Shape Model (ASM) modified by the motion vectors to detect and track the deformed human body for action. Active shape model is used to identify the particular shapes; it is also a training method. We use kinds of original human body model modified by motion vectors, instead of training result. Thus the active shape model can detect the human body after deformation. So that human body won't be lost or repeated detected. In this method, we use Optical-flow method to get the motion vectors. The function of the method is conformed by experiment and the detecting success rate of moving human body is 94%. The experimental results and discussion are also presented. (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS.2011.6045137 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-80055101511 (DOI: 10.1109/CCIS.2011.6045137, Elsevier: Scopus)
273.	Ye Liu and Fuji Ren : Japanese Named Entity Recognition for Question Answering System, Proc. of IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS 2011), 402-406, Beijing, Sep. 2011. (Summary) Current question answering (QA) systems usually contain named entity recognizer (NER) as a core component. NER is an important and difficult task in computational linguistics. It plays an important role in natural language processing application such as Question Answering, Machine Translation, and Information Retrieval etc. NER includes the identification and classification of certain proper nouns (like location, organization, person, data, money and others) in a text. The purpose of our study is to recognize and extract the exact Japanese sight seeing domain named entities. It is a basic step for the following processing: question analysis and keyword extraction information retrieval. As well as, through doing the named entity recognition, we consider that it can mine exact information from text document to respond to user. This paper describes how to do the Japanese sightseeing named entity recognition due to we are constructing a Japanese sightseeing question answering system. We adopt the hybrid method which combined with machine learning and rule-base method. In the experiment of Japanese sightseeing domain named entity recognition we have got excellent precision and recalling rates. It shows that our method is effective and can be used in a practical question answering system. (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS.2011.6045098 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-80055104477 (DOI: 10.1109/CCIS.2011.6045098, Elsevier: Scopus)
274.	Mengsi Cao, Guannan Fang and Fuji Ren : EEG-BASED EMOTION RECOGNITION IN CHINESE EMOTIONAL WORDS, Proc. of IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS 2011), 452-456, Beijing, Sep. 2011. (Summary) Emotion recognition is becoming a more and more hot topic nowadays. Many researches on facial recognition and speech recognition have been done. In this paper, we develop a method to facilitate emotion recognition with electroencephalographic (EEG) signals. The main objective of our study is to reveal the relation between emotional responses and EEG data gathered through giving seven subjects word-imagination stimuli. To induce emotions we choose 20 Chinese emotional words which have relatively high emotional intensities. We use support vector machine (SVM) and linear discriminant analysis (LDA) to recognize emotion, respectively, the average recognition rates of 48.78% and 57.04% could be achieved. (Link to Publication Site) ● Publication site (DOI): 10.1109/CCIS.2011.6045108 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-80055120579 (DOI: 10.1109/CCIS.2011.6045108, Elsevier: Scopus)
275.	Motoyuki Suzuki, Seiji Tsuchiya and Fuji Ren : A novel emotion recognizer from speech using both prosodic and linguistic features, Knowledge-Based and Intelligent Information and Engineering Systems, Vol.LNAI6881, 456-465, Sep. 2011. (Summary) Emotion recognition based on speech characteristics generally relies on prosodic information. However, utterances with different emotions in speech have similar prosodic features, so it is difficult to recognize emotion by using only prosodic features.In this paper, we propose a novel approach to emotion recognition that considers both prosodic and linguistic features. First, possible emotions are output by clustering-based emotion recognizer, which only uses prosodic features. Then, subtitles given by the speech recognizer are input for another emotion recognizer based on the Association Mechanism. It outputs a possible emotion by using only linguistic information. Lastly, the intersection of the two sets of possible emotions is integrated into the final result.Experimental results showed that the proposed method achieved higher performance than either prosodic- or linguistic-based emotion recognition. In a comparison with manually labeled data, the F-measure was 32.6%. On the other hand, the average of F-measures of labeled data given by other humans was 42.9%. This means that the proposed method performed at 75.9% in relation to human ability. (Keyword) Emotion recognition / prosodic feature / linguistic feature / association mechanism
276.	Kazuyuki Matsumoto and Fuji Ren : Construction of Wakamono Kotoba Emotion Dictionary and Its Application, Computational Linguistics and Intelligent Text Processing, Vol.LNCS6608, 405-416, Feb. 2011. (Summary) Currently, we can find a lot of weblogs written by young people. In the weblogs, they tend to describe their undiluted emotions or opinions. To analyze the emotions of young people and what causes those emotions, our study focuses on the specific Japanese language used among young people, which is called Wakamono Kotoba. The proposed method classifies Wakamono Kotoba into emotion categories based on superficial information and the descriptive texts of the words. Specifically,the method uses literal information used for Wakamono Kotoba, such as Katakana, Hiragana, and Kanji, etc., stroke count, and the difficulty level of the Kanji as features. Then we classified Wakamono Kotoba into emotion categories according to the superficial similarity between the word and the Wakamono Kotoba registered in the dictionary with an annotation of its emotional strength level. We also proposed another method to classify Wakamono Kotoba into emotion categories by using the cooccurrence relation between the words included in the descriptive text of the Wakamono Kotoba and the emotion words included in the existing emotion word dictionary. We constructed the Wakamono Kotoba emotion dictionary based on these two methods. Finally, the applications of the Wakamono Kotoba emotion dictionary are discussed. (Keyword) Wakamono Kotoba / emotion dictionary / emotion corpus
277.	Changqin Quan and Fuji Ren : An Exploration of Features for Recognizing Word Emotion, Proceedings of the 23rd International Conference on Computational Linguistics, 922-930, Beijing, Aug. 2010. (Summary) Emotion words have been well used as the most obvious choice as feature in the task of textual emotion recognition and automatic emotion lexicon construction. In this work, we explore features for recognizing word emotion. Based on Ren-CECps (an annotated emotion corpus) and MaxEnt (Maximum entropy) model, several contextual features and their combination have been experimented. Then PLSA (probabilistic latent semantic analysis) is used to get semantic feature by clustering words and sentences. The experimental results demonstrate the effectiveness of using semantic feature for word emotion recognition. After that, "word emotion components" is proposed to describe the combined basic emotions in a word. A significant performance improvement over contextual and semantic features was observed after adding word emotion components as feature.
278.	Nagai Yuko, Tetsuya Tanioka, Fuji Shoko, Yuko Yasuhara, Sakamaki Sakiko, Taoka Narimi, Rozzano De Castro Locsin, Fuji Ren and Kazuyuki Matsumoto : Needs and challenges of care robots in nursing care setting: A literature review, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 292-295, Beijing, Aug. 2010. (Summary) This study aims to identify needs and challenges of care robot in nursing care setting through an extensive search of the literature. As the result shows, there exists a shortage of information about results of the introduction of care robots, the needs of recipients and care providers, and relevant ethical problems. To advance our research and to introduce care robots into setting, there are so many things to do; consider the application of natural language processing technology by collaborating with researchers in the robotics field, carry out an investigation, extract the needs, clarify ethical problems and seek solutions, conduct the on-site experiment study, and so on. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2010.5587815 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-78649300264 (DOI: 10.1109/NLPKE.2010.5587815, Elsevier: Scopus)
279.	Date Mai, Tetsuya Tanioka, Yuko Yasuhara, Kazuyuki Matsumoto, Yukie Iwasa, Chiemi Kawanishi, Hirai Eri and Fuji Ren : The present conditions, problems and future direction of the server-controlled clinical pathway system development in psychiatric hospitals, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 296,303, Beijing, Aug. 2010. (Summary) Clinical pathways used today are paper-based, although many different kinds of clinical pathway are used in clinical practice. However, in the development of software for clinical pathway, it is difficult to achieve cooperation between medical experts, who are not used to expressing their ideas and work in words, and system-developers whose medical knowledge is limited. As a consequence, the current situation is that medical practitioners make their own software and use it in their practice. While this may work, it is less than ideal because refinements that may make the software most effective through engineering expertise is not used. Thus, in our research team, the nurse researchers and the engineering researchers cooperated and developed a clinical pathway system. In this paper, the present conditions, problems, and future direction of the server-controlled CP system development in the psychiatric hospitals, is discussed from viewpoint of nursing as a user. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2010.5587812 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-78649239475 (DOI: 10.1109/NLPKE.2010.5587812, Elsevier: Scopus)
280.	Haitao Yu, Fuji Ren, Degen Huang and Lishuang Li : Designing Effective Web Mining-Based Techniques for OOV Translation, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 337-344, Beijing, Aug. 2010. (Summary) Due to a limited coverage of the existing bilingual dictionary, it is often difficult to translate the Out-Of-Vocabulary terms (OOV) in many natural language processing tasks. In this paper, we propose a general cascade mining technique of three steps, it leverages OOV category to optimize the effectiveness of each step. OOV category based expansion policy is suggested to get more relevant mixed-language documents. OOV category based hybrid extraction approach is suggested to perform a robust extraction. A more flexible model combination based on OOV category is also suggested. Moreover, we conducted experiments to evaluate the effectiveness of each step and the overall performance of the mining technique. The experimental results show significantly performance improvement than the existing methods. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2010.5587807 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-78649242551 (DOI: 10.1109/NLPKE.2010.5587807, Elsevier: Scopus)
281.	Xiaodong Liu, Fuji Ren and Caixia Yuan : Use Relative Weight to Improve the kNN for Unbalanced Text Category, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 389-393, Beijing, Aug. 2010. (Summary) The technology of text category is widely used in natural language processing. As one of best text category algorithms, kNN is very popular used in many applications. Traditional kNN assumes that the distribution of training data is even, however, it is not the case for many situations. When we used kNN in our Topic Detection and Tracking (TDT) system, it did not perform well due to the bias of training data set. To overcome the obstacle caused by data bias, this paper proposes an approach which uses relative weight to adjust the weight of kNN (RWKNN). When evaluated on the data of TDT2 and TDT3 Chinese corpus, RWKNN proves to be robust on unbalanced data and yields better performance than the traditional kNN. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2010.5587799 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-78649287985 (DOI: 10.1109/NLPKE.2010.5587799, Elsevier: Scopus)
282.	Liping Wu, Song Liu and Fuji Ren : Chinese patent retrieval based on the pragmatic information, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 514-519, Beijing, Aug. 2010. (Summary) In this paper, we propose a novel information retrieval approach based on the pragmatic information for Chinese patents. At present, patent retrieval is becoming more and more important. Not only because patents are always can an important resource in all kinds of field, but patent retrieval save a great deal of time and funds for corporations and researchers. However, with available methods the precision of retrieval results for patents is not very high. What's more, through analyzed the patent documentations we found that except the literal meanings, there are deeper meanings which can be concluded from the patents. Here we call the deeper meanings as pragmatic information. Therefore we established a patent retrieval system to integrate the pragmatic information with classical information retrieval technique to improve the retrieval accuracy. Some experiments using the proposed method have carried out, and the results show that the precision of patent retrieval based on the pragmatic information is higher than the one without using it. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2010.5587776 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-78649242554 (DOI: 10.1109/NLPKE.2010.5587776, Elsevier: Scopus)
283.	Changqin Quan, Tingting He and Fuji Ren : Emotion Analysis in Blogs at Sentence Level Using a Chinese Emotion Corpus, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 427-434, Beijing, Aug. 2010. (Summary) Previous researches for emotional analysis of texts have included a variety of text contents: weblogs, stories, news, text messages, spoken dialogs, and so on. Compared with other text styles, the main characteristics of emotional expressions in blogs are as follows: (1) Highly personal, subjective writing style; (2) New words and expressions are constantly emerging; (3) The integrity and continuity of using language. Using a Chinese emotion corpus (Ren-CECps), in this study, we make an analysis on emotion expressions in blogs at sentence level. Firstly, we separate the sentences into two classes: simple sentences (sentences without negative words, conjunctions, or question mark) and complex sentences (sentences with negative words, conjunctions, or question mark). Then we compare the two classes of sentence on sentence emotion recognition based on emotional words. Furthermore we analysis the following factors for emotion change at sentence level: negative words, conjunctions, punctuation marks, and contextual emotions. At last, we make an hypothesis that the emotional focus of a sentence could be expressed by a certain clause in this sentence, and the experimental results have proved this hypothesis, which showed that selecting the clauses containing emotional focus of a sentence correctly would be helpful to recognize sentence emotions. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2010.5587790 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-78649308923 (DOI: 10.1109/NLPKE.2010.5587790, Elsevier: Scopus)
284.	Michihiro Jinnai, Yukio Akashi, Shinsuke Nakaya, Fuji Ren and Minoru Fukumi : Recognition of Abnormal Vibrational Responses of Signposts using the Two-dimensional Geometric Distance and Wilcoxon Test, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 166-173, Beijing, Aug. 2010. (Summary) In expressway companies, workers have been impacting signposts using wooden hammers and estimating the degree of the corrosion by listening to the sound. In order to automate this, we have been developing software that recognizes an abnormal impact vibrational response due to corrosion. This software extracts sonograms from impact vibrational waves using the LPC spectrum analysis, and matches images of the sonogram between a standard and an input impact vibrations using the Two-dimensional Geometric Distance. Then, the software distinguishes the abnormality of the input impact vibration using Wilcoxon rank-sum test. We have measured the impact vibrations of five normal signposts and five abnormal signposts, and carried out the automatic recognition experiments. As a result, the software has recognized correctly in all cases. We have verified the effectiveness of the proposed method. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2010.5587837 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-78649262406 (DOI: 10.1109/NLPKE.2010.5587837, Elsevier: Scopus)
285.	XIN KANG, Fuji Ren and Yunong Wu : Bottom Up: Exploring Word Emotions for Chinese Sentence Chief Sentiment Classification, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 422-426, Beijing, Aug. 2010. (Summary) In this paper we demonstrate the effectiveness of employing basic sentiment components for analyzing the chief sentiment of Chinese sentence among nine categories of sentiments (including No emotion). Compared to traditional lexicon based methods, our research explores emotion intensities of words and phrases in an eight dimensional sentiment space as features. An emotion matrix kernel is designed to evaluate inner product of these sentiment features for SVM classification with O(n) time complexity. Experimental result shows our method significantly improves performance of sentiment classification. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2010.5587793 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-78649273536 (DOI: 10.1109/NLPKE.2010.5587793, Elsevier: Scopus)
286.	Ye Wu and Fuji Ren : Improving Emotion Recognition from Text with Fractionation Training, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 368-374, Beijing, Aug. 2010. (Summary) Previous approaches of emotion recognition from text were mostly implemented under keyword-based or learning-based frameworks. However, keyword-based systems are unable to recognize emotion from text with no emotional keywords, and constructing an emotion lexicon is a tough work because of ambiguity in defining all emotional keywords. Completely prior-knowledge-free supervised machine learning methods for emotion recognition also do not perform as well as on some traditional tasks. In this paper, a fractionation training approach is proposed, utilizing the emotion lexicon extracted from an annotated blog emotion corpus to train SVM classifiers. Experimental results show the effectiveness of the proposed approach, and the use of some other experimental design also improves the classification accuracy. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2010.5587800 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-78649299436 (DOI: 10.1109/NLPKE.2010.5587800, Elsevier: Scopus)
287.	Ling Xia and Fuji Ren : Pragmatic Analysis Based Query Expansion for Chinese Cuisine QA Service System, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 470-477, Beijing, Aug. 2010. (Summary) This paper proposes a query expansion method for cooking question answering system based on pragmatic analysis. In our approach, the results of question analysis is used. The original queries are generated by means of the question subject, then the query terms are expanded based on pragmatic function. When submitting the expended queries to Google search engine to retrieve related passages, we get an overall improvement of 36.2% on the mean average precision. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2010.5587785 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-78649237735 (DOI: 10.1109/NLPKE.2010.5587785, Elsevier: Scopus)
288.	Cheng Wang, Changqin Quan and Fuji Ren : Maximum Entropy Based Emotion Classification of Chinese Blog Sentences, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 382-388, Beijing, Aug. 2010. (Summary) At present there are increasing studies on the classification of textual emotions. Especially with the rapid developments of Internet technology, classifying blog emotions has become a new research field. In this paper, we classified the sentence emotion using the machine learning method based on the maximum entropy model and the Chinese emotion corpus (Ren-CECps)*. Ren-CECps contains eight basic emotion categories (expect, joy, love, surprise, anxiety, sorrow, hate and anger), which presents us with the opportunity to systematically analyze the complex human emotions. Three features (keywords, POS and intensity) were considered for sentence emotion classification, and three aspect experiments have been carried out: 1) classification of any two emotions, 2) classification of eight emotions, and 3) classification of positive and negative emotions. The highest classification accuracies of the three aspect experiments were 90.62%, 35.66% and 73.96%, respectively. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2010.5587798 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-78649237316 (DOI: 10.1109/NLPKE.2010.5587798, Elsevier: Scopus)
289.	Jun Wang, Lei Li and Fuji Ren : An Improved Method of Keywords Extraction Based on Short Technology Text, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 398-403, Beijing, Aug. 2010. (Summary) Keywords are the critical resources of information management and retrieval, automatic text classification and clustering. The keywords extraction plays an important role in the process of constructing structured text. Current algorithms of keywords extraction have matured in some ways. However the errors of word segmentation which caused by unknown words have been affected the performance of Chinese keywords extraction, particularly in the field of technological text. In order to solve the problem, this paper proposes an improved method of keywords extraction based on the relationship among words. Experiments show that the proposed method can effectively correct the errors caused by segmentation and improve the performance of keywords extraction, and it can also extend to other areas. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2010.5587797 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-78649240334 (DOI: 10.1109/NLPKE.2010.5587797, Elsevier: Scopus)
290.	Takuo Henmi, Shengyang Huang and Fuji Ren : Wisdom Media CAIWA Channel based on Natural Language Interface Agent, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 12-19, Beijing, Aug. 2010. (Summary) Based on the breakthroughs in natural language interface agent CAIWA, web content distribution platform CAIWA Channel has been built for both PC and smatphone clients. The platform is regarded as wisdom media, since it seeks for providing information precisely what users demand, in addition to removing barriers of user interface bottlenecks. Not only recommendations of information to the user based on the past behavior, interest and profile, but also the CAIWA Channel has built-in evolution mechanism by proactively collecting information about the user in a natural manner via conversation with the user. It can accumulate knowledge for better meeting the user's personal requirements, while web contents are organized according to the user's interest. CAIWA Channel is not a mere information search system but a knowledge query system and a human-touch system incorporating emotional reactions. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2010.5587862 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-78649290182 (DOI: 10.1109/NLPKE.2010.5587862, Elsevier: Scopus)
291.	Yasushi Katsura, Kazuyuki Matsumoto and Fuji Ren : Flexible English Writing Support Based on Negative-Positive Conversion Method, Proceedings of IEEE NLP-KE2010, 499-505, Aug. 2010. (Summary) With development of the recent globalization, thechance to exchange in English increased in the business field.In particular, its necessary to write a thesis and a charterhandwriting in English. Because many Japanese are notused to making English sentence, it is a great burden towrite appropriate sentence in English without any supportfor creating English sentence. In this study we havedeveloped an English composition support system. By thissystem, its to search for the interlinear translation exampleto refer to by database and generate a new sentence byreplacing a noun in the example sentence. In this paper,based on the technique of Super-Function, we propose amethod to convert an affirmative sentence into negativesentence and vice versa to realize more flexible andextensive text conversion. (Keyword) Super-Function / English Writing System (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2010.5587778 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-78649288880 (DOI: 10.1109/NLPKE.2010.5587778, Elsevier: Scopus)
292.	Kazuyuki Matsumoto, Yusuke Konishi, Sayama Hidemichi and Fuji Ren : Wakamono Kotoba Emotion Corpus and Its Application for Emotion Estimation, Proceedings of 2010 International Conference on Advanced Intelligence, Vol.2, 89-99, Beijing, Aug. 2010. (Summary) In this paper, we describe how we constructed the linguistic resources of Wakamono Kotoba emotion corpus to be used for emotion recognition and explain the features we obtained from statistical analysis. Our Wakamono Kotoba emotion corpus includes Japanese language used by young people and language for expressing emotion. These were mainly gathered from Weblogs that were written by young people from their teens to their twenties. (Keyword) Emotion Recognition / Wakamono Kotoba / Emotion Corpus
293.	Yuko Nagai, Tetsuya Tanioka, Shoko Huji, Yuko Yasuhara, Sakiko Sakamaki, Narimi Taoka, C Rozzana Locsin, Fuji Ren and Kazuyuki Matusumoto : Needs and changes of robots in nursing care setting: A Literature review, Proceeding of IEEE2010, Aug. 2010. (Summary) This study aims to identify needs and challenges of care robot in nursing care setting through an extensive search of the literature. As the result shows, there exists a shortage of information about results of the introduction of care robots, the needs of recipients and care providers, and relevant ethical problems. To advance our research and to introduce care robots into setting, there are so many things to do; consider the application of natural language processing technology by collaborating with researchers in the robotics field, carry out an investigation, extract the needs, clarify ethical problems and seek solutions, conduct the on-site experiment study, and so on.
294.	Wei Wang, Motoyuki Suzuki and Fuji Ren : Texture Image Retrieval Based on Gray-Primitive Co-occurrence Matrix, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 199-202, Aug. 2010. (Summary) The research of texture similarity is very important component of content-based image retrieval system. Firstly the rotation invariance of gray-primitive co-occurrence matrix was proved in this paper, then a new texture image retrieval technique based on gray-primitive co-occurrence matrix was presented. The result of experiment indicates that the algorithm proposed has low computational complexity and certain noise resisting ability. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2010.5587830 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-78649282747 (DOI: 10.1109/NLPKE.2010.5587830, Elsevier: Scopus)
295.	Motoyuki Suzuki, Masashi Adachi, Minoru Kohata, Akinori Ito, Shozo Makino and Fuji Ren : An HMM-based segment quantizer and its application to low bit rate speech coding, Proc. International Congress on Acoustics, Sydney, Aug. 2010. (Summary) Several speech coding systems employ a segment quantizer instead of a vector quantizer. One of the most important problems is how to construct a segment codebook. In this paper, a new speech coder based on the ML-BEATS is proposed. The ML-BEATS is one of the HMM-based segment quantizer. First, it splits a vector sequence into several sub-sequences, and then these sub-sequences are clustered in order to construct a codebook. Each cluster center is represented by a left-to-right HMM. In the encoding process, input speech is matched with HMMs in the codebook, and then HMM index and duration information are sent to the decoder. In the decoding process, a decoded sequence is generated from HMM parameters by applying the HMM-based speech synthesis method. From the experimental results, the HMM-based speech coder gave 1.13 dB spectral distortion with 5.83 bit/frame. It is 0.11 dB higher spectral distortion than that given by G.729 coder, but bit rate decreased only 32%. In order to consider a shifting problem of LSP dimensions, we also propose a new codebook construction method. Many training vectors are extracted from training samples by shifting dimensions, and all vectors are used for constructing a universal codebook. The universal codebook can deal with any shifted vectors because all possibilities are included in the training data. From the experimental results, the shifted vector method encoded an input speech with very low bit rate, but it gave higher spectral distortions.
296.	Lei Yu and Fuji Ren : A Study on Cross-Language Text Summarization Using Supervised Methods, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 586-592, Dalian, Sep. 2009. (Summary) In this work, we use Hidden Markov Models (HMM), Conditional Random Field (CRF), Gaussian Mixture Models (GMM) and Mathematical Methods of Statistics (MMS) for Chinese and Japanese text summarization. The purpose of this work is to study the applicability of mentioned three trainable models for cross-language text summarization. For model training, we use several training features such as sentence position, sentence centrality, number of Name Entity and so on. For model testing, Chinese on-line news and Japanese news are used as test data which are extracted from web pages. We evaluate each model by measuring the precision at the compression rate 10%, 20% and 30%. MMS is a baseline method. The results show that HMM, CRF and GMM have remarkable increases than MMS on both Chinese and Japanese text summarization by using the same training features. Especially, GMM model make a best performance in all tests. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2009.5313809 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2009.5313809 (DOI: 10.1109/NLPKE.2009.5313809)
297.	Ruiqiang Guo and Fuji Ren : Towards the Relationship Between Semantic Web and NLP, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 578-585, Dalian, Sep. 2009. (Summary) With the development of Semantic the Web technology, the NLP technology has much broader prospects. This article analyses the fusion degrees between the two technologies based on the survey of relations of them. We explain the relationship between Semantic Web and NLP in two aspects. One is NLP how to support Semantic Web development in Ontology Learning, Ontology Query and Multilingual Ontology Mapping. The other is Semantic Web technologies how to improve NLP results in Information Extraction and Word Sense Disambiguation. We also propose some research challenges for the cooperation between Semantic Web and NLP. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2009.5313806 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2009.5313806 (DOI: 10.1109/NLPKE.2009.5313806)
298.	Yan Sun, Changqin Quan and Fuji Ren : Analysis on Degree Words for Chinese Emotion Expressions Based on Syntactic Parse and Rules, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 562-567, Dalian, Sep. 2009. (Summary) Analysis of emotions in texts has wide-ranging applications. In the analysis of emotional expressions, degree words are important for expressing emotion intensity of emotions. With the support of a large Chinese emotion corpus (Ren-CECps), in this paper, we present analysis on degree words for Chinese emotion expressions based on syntactic parse and rules. At first, Ren-CECps is used to extract the rules of degree words and their modifying elements. Then, we make a contrast analysis on emotion intensities of emotional words with and without modified by degree words. The quantity level for degree words is presented. Based on the extracted rules and quantity degree, a method of sentence parse is used to extract the modifying elements of degree words and to get the emotion intensity of emotional words when they are modified by degree words in sentences. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2009.5313826 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2009.5313826 (DOI: 10.1109/NLPKE.2009.5313826)
299.	Tianjiao Gu and Fuji Ren : Chinese Sentence Similarity based on Word Context and Semantic, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 535-539, Dalian, Sep. 2009. (Summary) Sentence similarity computing plays an important role in the nature language processing. Many different methods are proposed to calculate sentence similarity including word, semantic, syntax and so on. In this paper, we proposed a sentence similarity method for travel question answering system by combining the word context information and semantic similarity together. We searched a series of context structures for keywords in a sentence. Experiment has been carried out to show the effectiveness of our method. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2009.5313774 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2009.5313774 (DOI: 10.1109/NLPKE.2009.5313774)
300.	Fang Tian and Fuji Ren : Hyponymy Acquisition from Chinese Text by SVM, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 505-510, Dalian, Sep. 2009. (Summary) Hyponymy as one of semantic relation taxonomies provides a fundamental knowledge for natural language processing applications. In this paper, we propose a method for automatically learning hyponymy terms by machine learning technique from text for Chinese. Our method relies on hand-crafted hyponymy patterns, and uses the syntactic features to build a multiple classifier to identify novel hyponymy pairs (hyponym /hypernym or hypernym /hyponym) in a sentence by SVM. Experimental results show that the method is effective in acquiring hyponymy from Chinese free text. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2009.5313833 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2009.5313833 (DOI: 10.1109/NLPKE.2009.5313833)
301.	Changqin Quan and Fuji Ren : Recognizing Sentence Emotions Based on Polynomial Kernel Method Using Ren-CECps, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 478-484, Dalian, Sep. 2009. (Summary) Emotion recognition on text has wide applications. In this study we propose a method of emotion recognition at sentence level based on a relative large emotion annotation corpus (Ren-CECps). From this corpus, we get the emotion lexicons for the eight basic emotions (expect, joy, love, surprise, anxiety, sorrow, angry and hate). Statistics show that the emotion lexicons derived from Ren-CECps are used more often in real use of language for emotional expressions than HOWNET sentimental lexicons. Kernel methods are state-of-the-art for solving machine learning problems. Polynomial kernel (PK) method is used to compute the similarities between sentences and the eight emotion lexicons. Then the experiential knowledge derived from Ren-CECps is used to recognize whether the eight emotion categories are present in a sentence. This method obtain 62.7% F-measure. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2009.5313834 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2009.5313834 (DOI: 10.1109/NLPKE.2009.5313834)
302.	Yusuke Konishi, Ruifan Li and Fuji Ren : Designing a Japanese Idiom Education Support System for Overseas' Students, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 365-372, Dalian, Sep. 2009. (Summary) The Japanese idioms are phrases which two or more words combine and have the different meaning from the original word. Therefore, learning a Japanese idiom is difficult for Japanese language learners. We are developing a Japanese Idiom Education Support System for Overseas' Students to solve this problem. The main purposes of the system are to raise learner's interest of learning idiom, and to teach the right usage of an idiom. The main functions of this system are the function of Japanese idiom retrieval and teaching Japanese idiom. The learner can input the idiom into the system and the system can retrieve and display an explanation of the idiom. And the learner can input the situation into the system and the system can retrieve the idiom. In this paper, the outline of Japanese Idiom Education Support System for Over-sea's Students, the method of Japanese idiom retrieval, and the result of questionnaire is presented. A questionnaire did the survey on attitudes toward educational support system. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2009.5313789 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2009.5313789 (DOI: 10.1109/NLPKE.2009.5313789)
303.	Ye Wu and Fuji Ren : Simple Linguistic Processing Effect on Multi-label Emotion Classification, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 350-354, Dalian, Sep. 2009. (Summary) Emotion plays a significant role in human communications in our daily life. With progress in human-machine interface technology, recent research has placed more emphasis on the recognition of emotion reaction. Comparing to some other ideal experimental settings, blog posts online would be respond more to real-world events. And a huge resource of text-based emotion can be found from the World Wide Web nowadays. This paper reports a study to investigate the effectiveness of using SVM (Support Vector Machine) on linguistic features considering emotion keywords and negative words, and classify a collection of blog posts sentences tagged by one or more labels finally. Our results show that individual emotions can be clearly separated by the proposed approach. To the multi-label classification of emotion, it also obtained a higher accuracy rate than the baseline unigram approach using SVM. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2009.5313832 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-72249105272 (DOI: 10.1109/NLPKE.2009.5313832, Elsevier: Scopus)
304.	Elmarhumy Mahmoud, Fattah Abdel Mohamed and Fuji Ren : Automatic Text Classification using Modified Centroid Classifier, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 282-285, Dalian, Sep. 2009. (Summary) This work proposes an approach to address the problem of inductive bias or model misfit incurred by the centroid classifier assumption to enhance the automatic text classification task. This approach is a trainable classifier, which takes into account tfidf as a text feature. The main idea of the proposed approach is to take advantage of the most similar training errors to the classification model to successively update it based on a certain threshold. The proposed approach is simple to implement and flexible. The proposed approach performance is measured at several threshold values on the Reuters -21578 text categorization test collection. The experimental results show that the proposed approach can improve the performance of centroid classifier. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2009.5313757 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-72249100339 (DOI: 10.1109/NLPKE.2009.5313757, Elsevier: Scopus)
305.	Ji Li and Fuji Ren : A proposal for Creating a Chinese Emotion Thesaurus with Tag of Emotion Intensity, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 274-281, Dalian, Sep. 2009. (Summary) In recent years, researchers have begun to pay more attention to the emotion recognition in natural language processing. In order to help this pursuit, this paper proposes a semi-automatic approach to create a Chinese emotion thesaurus with tag of emotion intensity based on two kinds of language resources HowNet and Tongyici Cilin. As a basic emotion resource, the emotion thesaurus should be used to help the classification and recognition of emotion in Chinese. We present a new algorithm of the semantic similarity computation for aiding the emotion intensity computation between words. The experimental results on verbs prove that our approach is feasible and effective. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2009.5313814 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2009.5313814 (DOI: 10.1109/NLPKE.2009.5313814)
306.	Ling Xia, Zhi Teng and Fuji Ren : Answer Generation for Chinese Cuisine QA System, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 262-267, Dalian, Sep. 2009. (Summary) In this paper, we propose an approach on answer generation for cooking question answering system. We first review previous work of question analysis. Then, we give annotation scheme for knowledge database. Finally, we present the answer planning based approach for generate an exact answer in natural language. An evaluation has been conducted on natural language questions and the result shows that the system can satisfy user's demand. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2009.5313813 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-72249099436 (DOI: 10.1109/NLPKE.2009.5313813, Elsevier: Scopus)
307.	Ye Liu and Fuji Ren : Unknown Place Name Detection base on YamCha for Japanese Guidance QA system, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 207-211, Dalian, Sep. 2009. (Summary) We perform a research about Japanese sightseeing guidance question answering (QA) system. In this domain Web information retrieval approach is always being used. However for the Web information retrieval, Japanese unknown place word detection needs to be considered. Some famous places are known very well, such as "Kinkaku-ji", it can be recognized by morphological analysis. However, the recognition rate of Japanese complex place is so poor. Therefore, we proposed an approach of the Japanese unknown place word detection. We use YamCha, a tool based on support vector machines (SVMs). The goal is that we want to recognize the unknown sightseeing spots word from user's question. In the experiment of Japanese place word detection we have got excellent precision and recalling rates. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2009.5313824 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-72249096876 (DOI: 10.1109/NLPKE.2009.5313824, Elsevier: Scopus)
308.	Huana Li and Fuji Ren : The Study on Text Emotional Orientation Based on a Three-dimensional Emotion Space Model, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 119-124, Dalian, Sep. 2009. (Summary) In order to recognize human emotion, a three-dimensional (3D) emotion space model was established and used to identify the text emotional orientation visually and intuitively. An emotion dictionary contains informations of eight basic emotions, was built based on the emotion corpus. By using this emotion dictionary, emotion keywords which behave distributions of 3D structure can be projected into the emotion space. Emotion distributions were transformed into an emotion matrix. By analyzing the emotion matrix, not only binary classification of texts but also multi-emotion attributes can be investigated. The best precision 91% of a binary classification is obtained in this work. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2009.5313815 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2009.5313815 (DOI: 10.1109/NLPKE.2009.5313815)
309.	Hong Zhang, Fuji Ren and Degen Huang : Existential Negative Sentence Translation In Japanese-Chinese Machine Translation, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 78-82, Dalian, Sep. 2009. (Summary) There are lots of negative sentences in both Japanese and Chinese, which are varing from meanings and phrasings. Especially the negative sentences always express complex relationships in Chinese language. So it is easy to make ambiguity when translating Japanese into Chinese. At present, it's very common that the translation softwares sold on the market make errors due to wrong translation of the negative sentences. This paper investigates the difference of existential negative sentences in Chinese and Japanese, then formulates translation rules and comes up with several translation ways for existential negative sentences based on characteristics of Japanese sentences, the corresponding attributes of the terms, the phrasings of Chinese sentences and so on. When testing on 150 negative sentences, the experiment confirms the effectiveness of the method introduced in the paper. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2009.5313819 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2009.5313819 (DOI: 10.1109/NLPKE.2009.5313819)
310.	Xiao Sun, Fuji Ren and Degen Huang : Extended Super Function based Chinese Japanese Machine Translation, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 39-46, Dalian, Sep. 2009. (Summary) Research on machine translation has a long history and many methods and techniques have been proposed and developed. However, low quality of translation is still a major problem and many related problems remain unresolved. Super function based machine translation was proposed to perform translation without going through syntactic and semantic analysis as many machine translation systems usually do. In such way, the import of the errors caused by the syntactic and semantic analysis could be avoided and the readability of the translation is also guaranteed. We continue to extend the super function for the Chinese Japanese machine translation. The super function is divided into the super function for sentences and super function for phrases. The existing scope and definition of the variable for super function is also expanded. The base noun phrases and base verbal phrases are detected and considered when building the super function. The head noun in base noun phrase is treated as variable but the determinative modifiers in base noun phrases are treated as modificatory variables, meanwhile the determinative modifiers in base verb phrases are treated as modificatory variables to build the super function. The revised Levenshtein distance algorithm is proposed for evaluate and find the matching super functions in database for input sentences and the determinative modifiers. The proposed extended super function keeps the advantages of the super function but has less number of super functions for Chinese Japanese machine translation. From the experiment results, the extended super function is not only effective but also feasible and with considerable precision for Chinese Japanese machine translation. The extended super function can even translate long sentences with complex structure for which the completely matching super functions can not be found for translation. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2009.5313817 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2009.5313817 (DOI: 10.1109/NLPKE.2009.5313817)
311.	Kazuyuki Matsumoto, Junko Matsumoto and Fuji Ren : Construction of English Composition Support System Based on Conveying Emotion, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 125-132, Dalian, Sep. 2009. (Summary) With the increased demand for English communication, various styles of learning support methods have been proposed and provided to the Japanese learners. However, there are still many learners finding it hard to read, write and speak in English. Regardless of language difference, understanding the other's intention and emotional status accurately and expressing what they think or feel to the others appropriately are the important abilities for actual communication. This paper focuses on the linguistic performance ability especially to communicate emotion and introduce our prototype system that help describe the emotion in English. (Keyword) English Composition / English Wrting / Natrural Language Processing / Emotional Expression (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2009.5313802 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-72249109597 (DOI: 10.1109/NLPKE.2009.5313802, Elsevier: Scopus)
312.	Kazuyuki Matsumoto and Fuji Ren : Estimate Word Emotions Based on Part of Speech and Positional Information, The 5th International Conference on Intelligent Computing, Ulsan, Sep. 2009.
313.	Atsushi Sasaki, Masashi Adachi, Motoyuki Suzuki and Fuji Ren : Influence on Emotional Impression of Voice by Changing Prosodic Features, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 445-451, Dalian, Sep. 2009. (Summary) In this paper, investigate the relation between emotions represented by speech and features included in speech. There are two kinds of approaches in comparing experiment. Firstly, speech data are non-verbal such as white-noise, sine wave and vowel /a:/, so that investigate the relation between emotions and prosodic features only. Secondly, speech data include verbal information such as `ohayou'(hello), `usotsuki'(Ananias), so that investigate case speech data are words. Result of comparing shows the effect that of verbal information on emotions is strong, in case of words used this experiment. On the other hand, emotions felt by subjects are changed by variation of prosodic features in some words. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2009.5313796 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2009.5313796 (DOI: 10.1109/NLPKE.2009.5313796)
314.	Jia Ma, Motoyuki Suzuki and Fuji Ren : Detect the Possible Spokesperson with an Omni-directional Camera, in a Robot-human Communication System, Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering, 159-163, Dalian, Sep. 2009. (Summary) When the man-machine communication system faces many users at the same time, it becomes a question that how to discover the spokesperson. In the complex environment, the noise may cause some difficulties for the robot to recognize the sound commands. To solve this question, we try to use the camera on the robot to find out the spokesperson. In this research, we propose a new image processing method that using omni-directional camera. The robot may find out all the possible s spokesperson around it, by detecting the human body and its movement. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2009.5313810 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2009.5313810 (DOI: 10.1109/NLPKE.2009.5313810)
315.	Caixia Yuan and Fuji Ren : Accurate Learning for Chinese Function Tags from Minimal Features, Proceedings of the ACL-IJCNLP 2009 Student Research Workshop, 54-62, Singapore, Aug. 2009. (Summary) Data-driven function tag assignment has been studied for English using Penn Treebank data. In this paper, we address the question of whether such method can be applied to other languages and Treebank resources. In addition to simply extend previous method from English to Chinese, we also proposed an effective way to recognize function tags directly from lexical information, which is easily scalable for languages that lack sufficient parsing resources or have inherent linguistic challenges for parsing. We investigated a supervised sequence learning method to automatically recognize function tags, which achieves an F-score of 0.938 on gold-standard POS (Part-of-Speech) tagged Chinese text a statistically significant improvement over existing Chinese function label assignment systems. Results show that a small number of linguistically motivated lexical features are sufficient to achieve comparable performance to systems using sophisticated parse trees.
316.	Changqin Quan and Fuji Ren : Construction of a Blog Emotion Corpus for Chinese Emotional Expression Analysis, Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, 1446-1454, Singapore, Aug. 2009. (Summary) There is plenty of evidence that emotion analysis has many valuable applications. In this study a blog emotion corpus is constructed for Chinese emotional expression analysis. This corpus contains manual annotation of eight emotional categories (expect, joy, love, surprise, anxiety, sorrow, angry and hate), emotion intensity, emotion holder/target, emotional word/phrase, degree word, negative word, conjunction, rhetoric, punctuation and other linguistic expressions that indicate emotion. Annotation agreement analyses for emotion classes and emotional words and phrases are described. Then, using this corpus, we explore emotion expressions in Chinese and present the analyses on them.
317.	Fang Tian, Peilin Jiang and Fuji Ren : A Practical System of Domain Ontology Learning Using the Web for Chinese, The Fourth International Conference on Internet and Web Applications and Services, 298-303, Venice/Mestre, Italy, May 2009. (Summary) This paper proposes an ontology learning system model based on the Web search engine and Protege-OWL API, which emphasizes iterative learning approach by the extracted instances. We discuss taxonomic and non-taxonomic relationship learning separately in ontology learning system, and investigate the importance of verb plus noun phrase learning for extraction of activity concepts in Chinese. We also propose an algorithm of relevance measurement for extracting relation instances by binary keywords based on co-occurrence statistics. Finally, we build a practical system of ontology learning through learning relation instances of the Chinese festival ontology, and test the effectiveness of our method. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICIW.2009.50 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/ICIW.2009.50 (DOI: 10.1109/ICIW.2009.50)
318.	Ye Wu and Fuji Ren : A Corpus-based Multi-label Emotion Classification using Maximum Entropy, Proceedings of International Workshop on Natural Language Processing and Cognitive Science, 103-110, Milan, Italy, May 2009. (Summary) Thanks to the Internet, blog posts online have emerged as a new grassroots medium, which create a huge resource of text-based emotion. Comparing to other ideal experimental settings, what we obtained by modeling blogs would be more private, honest and polemic because web logs from the World Wide Web evolve and respond more to real-world events. In this paper, our corpus consists of a collection of blog posts, which annotated as multi-label to make the classification of emotion more precise than the single-label set of basic emotions. Employing a maximum entropy classifier, our results show that the emotions can be clearly separated by the proposed method. Additionally, we show that the micro-average F1-score of multi-label detection increase when the mount of available training data further increases. (Link to Publication Site) ● Publication site (DOI): 10.5220/0002169901030110 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.5220/0002169901030110 (DOI: 10.5220/0002169901030110)
319.	Ye Yang, Jiang Peilin, Fuji Ren and Seiji Tsuchiya : Classic Chinese Automatic Question, the 7th Mexican International Conference on Artificial Intelligence (MICAI 2008), 58-64, Mexico, Oct. 2008. (Summary) In this paper, we propose a practical question answering system for the "Analects of Confucius" based on the pragmatics information. The "Analects of Confucius" is a classic Chinese literature by the Confucian during the Warring States Period (476 B.C-221 B.C ). But the literature can not be categorized by topics and it has comprehensive meanings, not only the literal meanings and explicitly communicated meanings of the passages, but also deeper meanings and implicitly communicated meanings (Here, we call the deep meaning and implicitly communicated meaning as pragmatics information). Therefore we constructed a QA system, which aims to help understanding the ''Analects of Confucius'' correctly. According to the experiments, the pragmatics information based retrieval results are more accurate than the results based on the interpretations in modern language. (Link to Publication Site) ● Publication site (DOI): 10.1109/MICAI.2008.31 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/MICAI.2008.31 (DOI: 10.1109/MICAI.2008.31)
320.	Jia Ma, Motoyuki Suzuki and Fuji Ren : Speaker Detection Method for Autonomous Robot In Complex Communication Environment Based on Image Processing, ICAI 2008, 349-354, Beijing, Oct. 2008. (Summary) In order to provide a better man-machine communicationsystem, we hope the computer or the robot can understandand simulate humans' command. To solve this problem, weneed to enable the robot to recognize the speaker. However,in the realistic scene, the factors of the complexenvironment, such as the noise, may course somedifficulties to recognize the commands. So imitating theperformance of human, we try to use the eyes of the robotto solve the problem. In this research, we propose a newspeaker detection method based on image processing. Therobot might find and identified all the possible speakersaround it, by detecting the recognizing the peoples' faces. Itmight also find out the speaker who is speaking, by judgingwhether the possible speakers' mouth are acting. Using eyecameras and a omni-directional camera, we developed asystem and some experiments were conducted to verify thisnew system.
321.	Ling XIA, Zhi TENG and Fuji Ren : Question Classification in Chinese Restrictd-domain Based on SVM and Dictionay, IEEE NLP-KE 2008, 486-491, Beijing, Oct. 2008. (Summary) Question classification is very important for question answering. This paper presents our research work on automatic question classification through support vector machine approaches. Unlike the classification using only bag-of-word features, we exploit the domain knowledge and question-specific stop words in our model, and also present how to enrich bag-of-word approach by implementing feature attributes to facilitate the question categorization. When tested on the questions in cooking domain, our approach reaches an accuracy up to 86.34%, which promisingly outperforms the result of the baseline. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2008.4906776 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2008.4906776 (DOI: 10.1109/NLPKE.2008.4906776)
322.	Ji Li and Fuji Ren : Emotion Recognition from Blog Articles, IEEE NLP-KE 2008, 355-362, Beijing, Oct. 2008. (Summary) Suicide of college students has been a universal phenomenon in the world. And the phenomenon has become more and more sever because of the complex and drastic competitions. With the popularization of Internet and the development of information processing technologies, a lot of people have established their own blog Websites to write down their experiences and express their feelings at times. It will be very helpful if the computer can recognize the emotions expressed in blog pages automatically. And then it will be convenient for teachers or psychological consultants to monitor the affective information of college students and take measures for the depression prevention when necessary. Owing to the advances in affective computing and natural language processing, researches have begun to pay more attention to the emotion recognition in NLP all over the world. This paper outlines the approach we have developed to construct a blog emotion-recognizing system. It is based on the lexical contents of words and structural characteristics of blog articles. For the emotion computing of articles, two methods are proposed and the experimental results are compared and analyzed. Finally, the implications of the results are discussed for the future's direction of the research. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2008.4906757 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2008.4906757 (DOI: 10.1109/NLPKE.2008.4906757)
323.	Peilin JIANG, Fuji Ren and Nanning ZHENG : Advanced Emotion Categorization and Tagging, IEEE NLP-KE 2008, 249-254, Beijing, Oct. 2008. (Summary) Affective computing is attracting attentions as a popular growing field with many applications such as Kansei engineering, information retrieval and HCI. But until now the study of fine-grained theory of emotion is still a challenge. In this paper, a novel method to analyze emotion category is proposed according to the statistics of affective property in Dictionary of contemporary Chinese. These emotion categories are called complex emotion. Firstly, over 3,700 common affective words and their detailed explanations had been collected for an affective lexicon, then we analyze the consistent relationship in the affective lexicon and consequently 52 salient complex emotion states are categorized and tagged by a straightforward clustering algorithm. The complex emotions are compared to the traditional definitions of basic emotions in psychology and have been evaluated to be valid in the experiment. Moreover we also have tagged the semantic orientation for the collected words. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2008.4906814 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2008.4906814 (DOI: 10.1109/NLPKE.2008.4906814)
324.	Dong LIU, Changqin QUAN, Fuji Ren and Peng CHEN : Sentiment and Sentimental Agent Identification Based on Sentimental Sentence Dictionary, IEEE NLP-KE 2008, 169-173, Beijing, Oct. 2008. (Summary) This paper presents a method of sentiment and sentimental agent identification based on Chinese sentimental sentence dictionary. Our method can identify eight kinds of sentiment (including joy, sorrow, love, disgust, surprise, anxiety, anger and hate), and the main sentimental agent. Sentimental sentence dictionary is composed by some sentimental sentence patterns. And the sentiment of a candidate sentence is identified by calculating the consistency with the sentimental sentence patterns. Especially, using the sentimental sentence dictionary, we can get rid of the sentences without sentiment, but have sentimental words. According to sentiment words and expressions, the sentences which are not appeared in the sentimental sentence dictionary also can be identified. The experiments show that we can get precision of 84% for sentiment identification, and precision of 69% for sentimental agent identification. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2008.4906802 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2008.4906802 (DOI: 10.1109/NLPKE.2008.4906802)
325.	Tianjiao Gu and Fuji Ren : Question Matching based on Fuzzy Set, IEEE NLP-KE 2008, 150-155, Beijing, Oct. 2008. (Summary) Sentence similarity computing plays an important role in the question answering (QA) system. Because there are many question expressions for one meaning, we present a new approach to match question based on fuzzy set. In this paper, we establish a library of standard questions. Each standard question is relative with a series of Keywords. The main focus of this paper lies with matching of standard questions and questions asked by users. An experimental system based on the proposed method has been built, and the results of our experiments shows the proposed method is effective for question matching. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2008.4906799 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2008.4906799 (DOI: 10.1109/NLPKE.2008.4906799)
326.	Ye WU and Fuji Ren : Emotion Recognition Based on Negative Words and Pattern Matching for Chinese Negative Sentence, IEEE NLP-KE 2008, 145-149, Beijing, Oct. 2008.
327.	Hong ZHANG and Fuji Ren : Negative Expression Translation in Japanese and Chinese Machine Translation, IEEE NLP-KE 2008, 75-81, Beijing, Oct. 2008. (Summary) Because there are many differences between Chinese and Japanese about the nature, history, culture, life, manners and customs, it is natural that there are particular words in each language. It is necessary that these particular words meaning are mastered right and translated accurately in translation. Because of the complex corresponding relationship with Chinese in Chinese-Japanese machine translation, it is easy to occur a vagueness, due to the negative in the sentence, many mistranslations are caused by the commercial translation software. In this paper, we analyzed the negative expressionways in Chinese and Japanese languages to translate Chinese negative sentences by using the selection rules of Chinese negative words and position rules. If we translate the basic Japanese negative expression naide1 into Chinese, its meaning is mei2, bie. Translate nakute into Chinese, according to its negative meaning and grammatical rule, it may be translated into bu. In the current research, we investigated a rough use rules which abstracted from each typical examples including naide and nakute.
328.	Caixia YUAN, Xiaojie WANG and Fuji Ren : Exploiting Lexical Information for Function Tag Labeling, IEEE NLP-KE 2008, 67-74, Beijing, Oct. 2008.
329.	Xiao SUN, Fuji Ren and Degen Huang : Dual-chain Unequal-state CRF for Chinese New Word Detection and POS Tagging, IEEE NLP-KE 2008, 60-66, Beijing, Oct. 2008. (Summary) In Chinese language processing, new words are particularly problematic. It is impossible to get a complete dictionary as new words can always be created. We proposed a unified dual-chain unequal-state CRF model to detect new words together with their part-of-speech in Chinese texts regardless of the word types such as compound words, abbreviation, person names, etc. The dual-chain unequal-state CRF model has two state chains with unequal number of states. The unequal state chains could model flexible hierarchical lexical information for both Chinese new word detection and POS tagging, and also integrate complex context features like the global information. The experimental results show that the proposed method is capable of detecting even low frequency new words and their parts-of-speech synchronously with satisfactory results. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2008.4906786 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2008.4906786 (DOI: 10.1109/NLPKE.2008.4906786)
330.	Changqin QUAN, Fuji Ren, Tingting He and Po Hu : Automatic Construction of Biomedical Abbreviations Dictionary from Text, IEEE NLP-KE 2008, 49-53, Beijing, Oct. 2008. (Summary) The size and growth rate of biomedical abbreviation are increasing very fast, automatic construction of biomedical abbreviations dictionary from text helps to understand biomedical literature, and to update existing databases, ontologies, and dictionaries. This paper proposes a new method for automatic construction of biomedical abbreviations dictionary from text by combining string matching algorithm and searching algorithm. The string matching algorithm extracts abbreviations and their longforms. The searching algorithm corrects the false longforms produced by the string matching algorithm. The searching algorithm is based on the idea that readers often lookup relative articles to judge the longform of an abbreviation is correct or not. Our experiments show that the algorithm has high precision (97.5%) and recall (82.2%). And because tagged corpus is not necessary, the method has high efficiency. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2008.4906784 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2008.4906784 (DOI: 10.1109/NLPKE.2008.4906784)
331.	FATTAH ABDEL Mohamed and Fuji Ren : Probabilistic Neural Network Based Text Summarization, IEEE NLP-KE 2008, 43-48, Beijing, Oct. 2008. (Summary) This work proposes an approach to address the problem of improving content selection in automatic text summarization by using probabilistic neural network (PNN). This approach is a trainable summarizer, which takes into account several features, including sentence position, positive keyword, negative keyword, sentence centrality, sentence resemblance to the title, sentence inclusion of name entity, sentence inclusion of numerical data, sentence relative length, Bushy path of the sentence and aggregated similarity for each sentence to generate summaries. First we investigate the effect of each sentence feature on the summarization task. Then we use all features in combination to train the probabilistic neural network (PNN) in order to construct a text summarizer model. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2008.4906783 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2008.4906783 (DOI: 10.1109/NLPKE.2008.4906783)
332.	Kaiyan HUANG, Yun Li and Fuji Ren : Generating Lexico Pattern for Dimensioning of Chinese Separable Verb-object Words in Chinese Text, IEEE NLP-KE 2008, 9-14, Beijing, Oct. 2008. (Summary) In this paper, we pay attention to the Chinese separable verb-object words in sentences. We collect sentences with morphemes of separable words employing search engine for thousands of separable words collected by linguist. Then sentences are tagged artificially with agreement of whether being used separable words on the result of word segmentation and part-of-speech tagging, According to typical grammar patterns discovered by linguists and patterns shared among collected sentences, lexical patterns are generated and optimized for further process of separable word tagging in Chinese document after word segmentation and part-of-speech tagging. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2008.4906778 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2008.4906778 (DOI: 10.1109/NLPKE.2008.4906778)
333.	Nadira Begum, Fattah Abdel Mohamed and Fuji Ren : STATISTICAL MODEL BASED TEXT SUMMARIZATION, ICAI 2008, 219-223, Beijing, Oct. 2008. (Summary) This work investigates different text features to select thebest one and proposes an approach to address automatic textsummarization. This approach is a trainable summarizer,which takes into account several features, including sentenceposition, sentence centrality, sentence resemblance to the title,sentence inclusion of name entity, sentence inclusion ofnumerical data and sentence relative length for each sentenceto generate summaries. First we investigate the effect of eachsentence feature on the summarization task. Then we use allfeatures score function to train feed forward neural network(FFNN) in order to construct a text summarizer for this model.The proposed approach performance is measured at severalcompression rates on a data corpus composed of 50 Englisharticles from the domain of politics.
334.	Xin Kang, Xiaojie Wang, Yongmei Tan and Fuji Ren : A Simple Method Improving Precision of Cross Domain Bilin-gual Sentence Alignment, ICAI 2008, 204-210, Beijing, Oct. 2008. (Summary) In this paper, we present three models distinguished by combining different language features, for the task of cross domain Chinese-English sentence alignment. The separat-ing capability of each single and combination of these fea-tures are compared, with further discussion of influences on performance. For each feature we introduce a polarity pa-rameter to measure the distinction between aligned pairs and other candidate pairs. Finally, thresholds are set to po-larities to further enhance performance precision (from 98.00% to99.69%).
335.	Liping Mi, Xin Luo and Fuji Ren : AN ERP RESEARCH ON CHINESE JAPANESE LEARNERS' PROCESSING OF JAPANESE KANJI AND SENTENCES, ICAI 2008, 14-19, Beijing, Oct. 2008. (Summary) This paper aims to investigate the recognition process ofJapanese Kanji and sentences for Chinese Japanese learners(CJL) by analyzing the event-related potential (ERP)differences between CJL and JNS (Japanese nativespeakers) while they visually recognized Japanese Kanjiand sentences. The experiment results showed that nosignificant differences were found between the two groupsin the Japanese Kanji condition, but the differences werefound in the Japanese sentences conditions. The N400latency for JNS appeared earlier, and the amplitude wasbigger than CJL, but the duration for CJL was longer thanthat for JNS. These results demonstrated that the difficultydegree for CJL was bigger than that for JNS on thesemantic processing of Japanese sentences. The P600appeared broadly following the N400 component for JNS,in contrast, the P600 only appeared over the right frontallobe for CJL. This demonstrated that the neuralmechanisms of recognition process of Japanese sentencesbetween the two groups were not identical. JNS alsoperformed syntactic processing after completed semanticprocessing. From the results, for CJL, the difficulty ofJapanese language learning was the recognition andunderstanding of Japanese sentences which includinghiragara, not Japanese Kanji.
336.	Li Yun, Huang Kaiyan, Seiji Tsuchiya, Fuji Ren and Zhong Yixin : Exploring Words with Semantic Correlations from Chinese Wikipedia, IIIP 2008, 103-108, Beijing, Oct. 2008. (Summary) In this paper, we work on semantic correlation between Chinese words based on Wikipedia documents. A corpus with about 50,000 structured documents is generated from Wikipedia pages. Then considering of hyper-links, text overlaps and word frequency, about 300,000 word pairs with semantic correlations are explored from these documents. We roughly measure the degree of semantic correlations and find groups with tight semantic correlations by self clustering. (Link to Publication Site) ● Publication site (DOI): 10.1007/978-0-387-87685-6_14 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1007/978-0-387-87685-6_14 (DOI: 10.1007/978-0-387-87685-6_14)
337.	Seiji Tsuchiya, Osaka Kyoko and Fuji Ren : A METHOD OF EMOTION JUDGEMENT IN EMPATHETIC UNDERSTANDING, ICAI 2008, 130-133, Beijing, Oct. 2008. (Summary) Purpose of this study is to judge human emotions frombrain activity of physiological phenomenon. Especially,we focus to empathetic understanding which is psychologicaltechnique. In this paper, we propose a empathyjudgement technique using subjective evaluation usingquestionnaire and objective evaluation using brainwaves measured by EEG. In results of experiment, itturns out that to judge empathy is difficult in the subjectiveevaluation using questionnaire and to judge empathyis possible in the objective evaluation using brainwaves. In addition, it turns out that emotions judgedfrom questionnaire and from brain waves are different.Thus, empathy judgement using both results generatea synergistic effect.
338.	Ye Yang, Fuji Ren and Seiji Tsuchiya : ANALECTS OF CONFUCIUS SELF-LEARNING SYSTEM USING PRAGMATICS AND TOPIC, ICAI 2008, 419-423, Beijing, Oct. 2008. (Summary) The purpose of this study is to construct a new selflearningsystem that supports the Analects of Confuciuslearning for the entry-level learner. We presentpragmatics and topic information to the learner. Thereare two roles of pragmatics and topic information. Thefirst one is to clarify the verse semantic and the secondis to make Analects of Confucius contents familiar tothe learner. The experiments evidenced the effectivenessof the presented pragmatics and topic informationthat is specific to increase enthusiasm for learning andenhance understanding of the contents.
339.	ADACHI Masashi, Seiji Tsuchiya and Fuji Ren : EMOTION INFERENCE METHOD BASED ON WORD'S MEANING AND UTTERANCE FEATURES, ICAI 2008, 138-141, Beijing, Oct. 2008. (Summary) Emotion recognition is necessary to realize smooth communicationbetween human and computer. This studyproposes an emotion prediction method based on twocommunication measures: words and utterances. Concretely,we investigate the emotions caused by meaningfulexpressions such as arigato (Thank you.) andbaka (Stupid.). Features of utterance such as utterancespeed, maximum value of power and the highestbasic frequency are extracted from four speeches. In thecase of male utterance, we learned that invoking emotionsof the listener was defined by the only utterancespeed regaredless of words meaning. But, in the caseof female utterance, we learned that invoking emotionsof the listener was defined by the utterance speed andmaximum of power regaredless of words meaning.
340.	Kyoko Osaka, Seiji Tsuchiya, Fuji Ren and Tetsuya Tanioka : A ANALYSIS OF EMPATHETIC UNDERSTANDING USING RELATION BETWEEN ELECTRODE AND FREQUENCY, ICAI 2008, 116-121, Beijing, Oct. 2008. (Summary) In this research, we propose technique to judge havingempathic understanding or not which compared subjectiveemotions of the subjects to estimate from questionnaireand objective emotions of the subject to estimatefrom brain waves measured by EEG. Specifically, subjectswatched trailer of the movies and assume baselinesthat watching trailer and compare the control groupthat did not give instructions with the experimentalgroup whom we directed to empathic understanding.
341.	MISHINA Kenichi, Seiji Tsuchiya and Fuji Ren : COMPARISON BETWEEN THE HUMAN EMOTION TRANSFER RATIO AND THE SIMILARITIES OF EMOTION, ICAI 2008, 126-129, Beijing, Oct. 2008. (Summary) Existing methods to recognize emotions of a sentence canrecognize a few kinds of emotion, and many methods use adictionary that emotion weights is related every words. Ouraims are to propose a method which can recognize with highprecision using feeling expression and can add new recognizableemotion easily. To realize the proposed method, weproposed an emotion similarity calculation. This method calculatessimilarity between emotions that two sentences represented.In the emotion similarity calculation, emotion similaritybetween an input sentence and classified sentence byemotions is used. The classified sentences are in emotioncorpora. The calculation formula is based on BLEU whichis a machine translation evaluation method. In this paper,an emotion similarity calculation method using N-gram frequencydictionaries is shown. This method can recognizewith high precision compared to the past one. The N-gramfrequency dictionaries are made from each emotion corpora.To examine the recognition accuracy with our method, wecompared the precision and the human emotion transfer ratiobetween humans. As a result, we found the precision is89.91% of the ratio. This result means the recognition withour method can recognize like a human.
342.	HAKAMATA Ai, Fuji Ren and Seiji Tsuchiya : Human Emotion Model based on Discourse Sentence for Expression Generation of Conversation Agent, IEEE NLP-KE 2008, 235-242, Beijing, Oct. 2008. (Summary) There was a conversation agent on the generation method of facial expression. It is necessary for the conversation system like the human for communication. In the previous method, at first a word which could influence the feeling was defined. Facial expression was changed according to the word which influences the feeling in discourse. Whereas, facial expression could not be changed if there was not a word that was defined in the discourse. Hence, we proposed a human emotion model for the expression generation of the conversation agent. The method based on the human emotion model can solve problem of the previous method and may make a more humanity conversation agent. In this study, we put a human emotion tag to discourse of talks scenarios and model to conversation agent of human emotion. There were two kinds of methods that put the human emotion tag to discourse. We make the human emotion model by scenarios that adopts the human emotion tag. Used the human emotion model to create facial expression of conversation agent. The assessment experiment was performed by using the systems of previous method and two human emotion models, and compared the results between the three methods. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2008.4906812 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2008.4906812 (DOI: 10.1109/NLPKE.2008.4906812)
343.	Fattah Abdel Mohamed and Fuji Ren : Support Vector Machine based Text Summarization, PROCEEDINGS OF ICCTA, 423-427, Cairo, Egypt, Oct. 2008. (Summary) This work investigates different text features toselect the best one and proposes an approach to addressautomatic text summarization. This approach is a trainablesummarizer, which takes into account several features,including sentence position, sentence centrality, sentenceresemblance to the title, sentence inclusion of name entity,sentence inclusion of numerical data, sentence relative length,Bushy path of the sentence and aggregated similarity foreach sentence to generate summaries. First we investigate theeffect of each sentence feature on the summarization task.Then we use all features score function to train SupportVector Machine (SVM) in order to construct a textsummarizer model. The proposed approach performance ismeasured at several compression rates on a data corpuscomposed of 100 English articles from the domain of politics. (Keyword) Automatic Summarization / Support Vector Machine / Text Features
344.	XIN KANG, Wang Xiaojie, Tan Yongmei and Fuji Ren : A Simple Method Improving Precision of Cross Domain Bilingual Sentence Alignment, International Conference on Advanced Intelligence (ICAI-08), 204-210, Oct. 2008.
345.	XIN KANG, Wang Xiaojie and Fuji Ren : Exploiting Syntactic and Semantic Information in Coarse Chinese Question Classification, The 4th IEEE International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE), 1-7, Oct. 2008. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2008.4906803 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-67650361209 (DOI: 10.1109/NLPKE.2008.4906803, Elsevier: Scopus)
346.	Kazuyuki Matsumoto, Junko Minato, Seiji Tsuchiya and Fuji Ren : An Approach for Evaluating Emotion Tagged Corpus, IADIS International Conference Interfaces and Human Computer Interaction 2008, 258-262, Amsterdam, Jul. 2008. (Summary) This paper proposes a method for evaluating our emotion corpus and describes the result of evaluation. The emotion corpus was originally created in Japanese and English to be used for emotion recognition research and consisted of dialogue sentences including emotional expressions. To ensure the reliability and use the corpus as the standard of emotion evaluation, the objective evaluation is necessary because single person annotated tags on the corpus. For Japanese part of corpus evaluation, we conducted a questionnaire to the several examinees. The examinees were asked to tag arbitrarily emotion categories on the sentences in the corpus. The obtained sentence emotion tags were classified then the match rate of the initial tag and the tags annotated by the examinees. Reliability of each emotion tag annotated on the sentence was calculated and added as emotional weight on each sentence emotion tag. The 10-fold cross validation test was conducted using the weight added corpus to estimate sentence emotion and obtained recall of 0.62 on average. (Keyword) Emotion Tagged Corpus / Emotion Recognition / Corpus Evaluation
347.	Obayashi Katsuyuki, Satoru Tsuge, Minoru Fukumi, Seiji Tsuchiya, Ryosuke Sumitomo, Fuji Ren and Shingo Kuroiwa : A Study of speaker identification using phoneme-information, NCSP'08, 164-167, Gold Coast, Mar. 2008.
348.	Kazuyuki Matsumoto, Junko Minato, Seiji Tsuchiya and Fuji Ren : An Algorithm for Extracting Emotion Occurrence Sentence Pattern from Corpus, Proceedings of 2008 AIAC Symposium, 109-123, Tokushima, Mar. 2008. (Summary) In this paper, we propose a method of extracting sentence patterns for estimating speaker's emotion.Our method estimates speaker's emotion by using a dictionary that registered the sentence pattern extracted from sentences expressing speaker's emotion.Because sentence types expressing emotion are various, we focused on dialogue sentence that includes important elements such as subject or object and proposed a method to extract the sentence pattern automatically.This paper describes the accuracy for converting the sentence including emotional expressions into the sentence patterns.We conduct experiments for emotion estimation based on the sentence pattern then describe the result of the evaluation. (Keyword) emotion estimation / sentence pattern / automatic extraction / corpus
349.	Fattah Abdel Mohamed and Fuji Ren : Automatic Text Summarization, PROCEEDINGS OF WORLD ACADEMY OF SCIENCE, ENGINEERING AND TECHNOLOGY, 192-195, Cairo, Egypt, Feb. 2008. (Summary) This work proposes an approach to address automatic text summarization. This approach is a trainable summarizer, which takes into account several features, including sentence position, positive keyword, negative keyword, sentence centrality, sentence resemblance to the title, sentence inclusion of name entity, sentence inclusion of numerical data, sentence relative length, Bushy path of the sentence and aggregated similarity for each sentence to generate summaries. First we investigate the effect of each sentence feature on the summarization task. Then we use all features score function to train genetic algorithm (GA) and mathematical regression (MR) models to obtain a suitable combination of feature weights.
350.	Fattah Abdel Mohamed and Fuji Ren : English-Arabic Transliteration, 6th WSEAS International Conference on CIRCUITS, SYSTEMS, ELECTRONICS,CONTROL & SIGNAL PROCESSING, 597-602, Cairo, Egypt, Dec. 2007.
351.	Fuji Ren : Framework of Affective Information Processing for Next Generation Communications, Proceedings of 2007 National Conference on Artificial Intelligence, 26-29, Harbin, China, Dec. 2007. (Summary) The extraction and recognition task of affective information are attracting researchers in order to realize emotion communications between machine and human beings. Human psychological characteristics are focused on to develop general-purpose agents that can complete the task of human emotion recognition and machine emotion generation. In this case, we comprehensively analyze the features such as brain waves, voice sounds and images that represent information included in emotion elements of phonation, facial expressions, and speech usage. We analyze and estimate many statistical data based on the latest achievements of brain science and psychology in order to derive transition networks for human psychological states. A multimedia and multifunction project for emotion recognition, estimation and representation is improving through establishing a speaker word model for researching psychological change and emotional presentation, proposing a new approach for recognizing human emotion based on Mental State Transition Network, and developing one emotion estimation method based on sentence pattern of emotion occurrence events.
352.	Jiang Peilin, Ma Jia, Minamoto Yusuke, Seiji Tsuchiya, Ryosuke Sumitomo and Fuji Ren : Orient video database for facial expression analysis, Proceeding of the 10th IASTED International Conference Intelligent Systems and Control, 211-214, Massachusetts, Nov. 2007. (Summary) The research on affective computing and related applications are attracting attentions during the last decades, particularly in Japan with the development of e-business. In this case, the human facial expression data is necessary to studies of emotion recognition and synthesis. There are many famous existed facial expression databases but they are primarily composed by Europeans or American subjects. The cultural background differences generate the gap between their styles of emotion expression. For an instance, comparing to the Europeans, the orient like Japanese do not have obvious facial expression. In this paper we propose a human facial expression video database named as AONE (Asian Oriental Expression) for orient in order to analyze and recognize the emotion automatically through human facial expression. We established the database of 75 adults mainly from orient, which included more 2000 samples of video sequences of facial expression from both frontal and side view. By consideration of the existed famous facial expression databases such as KANADE database form CMU, we designed the database containing both the spontaneous and deliberate facial expressions.
353.	Junko Minato, Kazuyuki Matsumoto, Seiji Tsuchiya, Shingo Kuroiwa and Fuji Ren : Comparison of corpus-based emotion estimation methods, Proceeding of the 10th IASTED International Conference Intelligent Systems and Control, 235-239, Massachusetts, Nov. 2007. (Summary) Internationalization of information is increasing needs for a computer to deal with multilingual communication. Understanding not only semantic information but also underlying emotion in textual information can contribute to assist such communication and also to make human-computer interaction more natural and congenial. For the purpose of emotion estimation from multilingual text, we created bilingual emotion annotated corpus in Japanese and English. Based on the corpus, we statistically analyzed the characteristics of how word emotion affects sentence emotion in each language. Two kinds of emotion estimation methods were proposed by using the existing techniques considering the feature quantity obtained from the corpus statistics then evaluation experiments were carried out. (Keyword) Corpus analysis / Affective computing / Statistic analysis / Emotion estimation
354.	Lipin Mi, Fuji Ren, Hideo Araki, Shingo Kuroiwa and Katurori Sano : The differences in Japanese language processing between Japanese and Chinese:Evidence from event-related potential, IEEE NLP-KE2007 Poster Session, 216-221, Beijing, Aug. 2007.
355.	Takanori Hirai, Satoru Tsuge, Shingo Kuroiwa and Fuji Ren : A speech emphasis method for noise-robust speech recognition by using repetitive phrase, IEEE NLP-KE2007 Poster Session, 140-144, Beijing, Aug. 2007. (Summary) In this paper, we propose a novel noise-robust speech recognition technique using a repetitive phrase such as "Turn on the TV, Turn on the TV" as a speech command to control household appliance apparatus and on-vehicle apparatus. In daily conversation,the use of repetitive phrase with many syllable gives a low appearance ratio, and reduces the incorrect acceptance of a command. Moreover, speech emphasis may be expected by using repetitive phrase because each phrase is not influenced by unexpected noise at same time. In this paper, we propose to use repetitive phrase as speech emphasis. We conduct speech recognition experiment using the speech which are degraded by three kinds of noises: a buzzer, a whistle, and a telephone ring. From this experiment, we proposed method can improve the speech recognition accuracy under the condition of the all noises. Especially, the proposed method improves the speech recognition accuracy (from 25% to 86%) under the condition of the whistle noise. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICCT.2006.341938 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/ICCT.2006.341938 (DOI: 10.1109/ICCT.2006.341938)
356.	Hua Xiang, Peilin Jiang, Shuang Xiao, Fuji Ren and Shingo Kuroiwa : An Affective Virtual Character Based on the Mental State Transition Network, IEEE NLP-KE2007 Poster Session, 117-122, Beijing, Aug. 2007.
357.	Ryosuke Sumitomo, Kaoru Ohya, Hitoshi Tanaka and Fuji Ren : Designing of Campus Information Navigator based on Human-Machine Dialog, IEEE NLP-KE2007 Poster Session, 111-116, Beijing, Aug. 2007.
358.	Peilin Jiang, Fuji Ren, Nanning Zheng, Ran Li and Shingo Kuroiwa : Nolinear Luminance-Chrominance Spase Map based Speak Detection by Hidden Markov Model, IEEE NLP-KE2007 Poster Session, 105-110, Beijing, Aug. 2007.
359.	Liying Mi, Xin Luo, Fuji Ren and Shingo Kuroiwa : Super-Function Matching of Causative Sentences for Chinese-Japanese Machine Translation, IEEE NLP-KE2007 Poster Session, 47-54, Beijing, Aug. 2007.
360.	Yu Zhang, Fuji Ren and Shingo Kuroiwa : Construction and Analysis of an Chinese Emotion Corpus, IEEE NLP-KE2007 Poster Session, 41-46, Beijing, Aug. 2007. (Summary) This paper presents an effective and practical approach on the emotional lexicographic component of Chinese documentation. Most previous works have focused on identifying emotion according to affective computing. In this paper, we will focus on constructing and analyzing one part of our emotion thesaurussentence corpus. Additionally, an automatic sentence gathering tool and a sentence corpus are developed.
361.	Jiaiun Yan, Bracewell B. David, Fuji Ren and Shingo Kuroiwa : A Hybrid Approach to Determiniing Semantic Dependency Relations of Chinese Sentences, IEEE NLP-KE2007 Poster Session, 7-13, Beijing, Aug. 2007.
362.	Hisazumi Katsutoshi, Seiji Tsuchiya, Shingo Kuroiwa and Fuji Ren : Extraction of the term which has an explicit relation using Coincidence Frequency, IEEE NLP-KE2007 Poster Session, 178-183, Beijing, Aug. 2007.
363.	Mishina Kenichi, Seiji Tsuchiya, Shingo Kuroiwa and Fuji Ren : An Emotion Similarity Calculation Using N-gram Frequency, IEEE NLP-KE2007 Poster Session, 160-165, Beijing, Aug. 2007.
364.	Ma Jia, Seiji Tsuchiya, Shingo Kuroiwa, Fuji Ren and Yu Lei : The New Image Processing Method in Expression Recognition System, IEEE NLP-KE2007 Poster Session, 134-139, Beijing, Aug. 2007.
365.	Lin Ye, Fuji Ren, Shingo Kuroiwa and Seiji Tsuchiya : Similarity Computing Based on VSM and Syntactic Analysis, IEEE NLP-KE2007 Poster Session, 61-65, Beijing, Aug. 2007.
366.	Mitsuhiro Ozawa, Satoru Tsuge, Masami Shishibori, Kenji Kita, Minoru Fukumi, Fuji Ren and Shingo Kuroiwa : Automatic Utterance Segmentation Tool for Speech Corpus, IEEE NLP-KE2007, 401-406, Beijing, Aug. 2007. (Summary) We collect the speech data for investigating an intra-speakers' speech variability over a short and long time. In general, to reduce the load of speakers, the speech data are collected as one file from collecting start to collecting end. Hence, there are some noises, non-speech sections and mistaken sections in this file. Consequently, we must segment this file into individual utterances and select the useful utterances. This process requires a lot of time and efforts. In this paper, we propose an automatic utterance segmentation tool for dividing the collected speech data. The proposed tool is composed of four processes, which are a voice activity detection, speech recognition, a DP matching, and a correct of speech section. For evaluating the proposed tool, we conduct the evaluation experiments using a female speaker's speech data in our corpus. Experimental results show that the proposed method can reduce a filing time by 90% compared to a manual filing. In This paper, first, we introduced the large speech corpus. This speech corpus contains is the speech data collected by specific speaker over long and short time periods. And, we explained the automatic utterance segmentation tool which we made in the case of corpus build. And inspected the validity. As a result, it was demonstrated that the automatic utterance segmentation tool was high-performance. Furthermore, it was demonstrated that speech corpus build became simple by using the automatic utterance segmentation tool. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2007.4368062 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-47749136580 (DOI: 10.1109/NLPKE.2007.4368062, Elsevier: Scopus)
367.	Satoru Tsuge, Keiji SEIDA, Masami Shishibori, Kenji Kita, Fuji Ren, Minoru Fukumi and Shingo Kuroiwa : Analysis of Variation on Intra-Speakers Speech Recognition Performances, IEEE NLP-KE2007, 387-392, Beijing, Aug. 2007. (Summary) Even if a speaker uses a speaker-dependent speech recognition system, speech recognition performance varies. However, the relationships between intra-speaker's speech variability and speech recognition performance are not clear. To investigate these relationships, we have been collecting speech data since November 2002. In this paper, we analyze the relationships between intra-speaker's speech variability and the phoneme accuracy by a correlation analysis. Analyzed results showed the strong negative correlation between the phoneme accuracy and the speaking rate. The correlation coefficient indicated -0.77. Moreover, we can see that the phoneme accuracy is correlated with the temperature in the recording room and the humidity difference. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2007.4368060 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2007.4368060 (DOI: 10.1109/NLPKE.2007.4368060)
368.	Tetsuya Tanioka, Ai Kawamura, Kazuyuki Matsumoto, Kazushi Mifune, Yoichiro Takasaka, Kyoko Osaka, Shuichi Ueno, Rozzano De Castro Locsin, Mutsuko Kataoka, Takuya Matsuda, Fuji Ren and Toshiko Tada : Outcome Management and Morphologic Variance Analysis Using PsychomsTM for Patient Care in Psychiatric Hospitals, IEEE NLP-KE2007, 502-506, Beijing, Aug. 2007. (Summary) In 2003, the Japanese government set an approximate goal of 72,000 social hospitalization in-patients being discharged in 10 years from psychiatric hospitals to the community. To meet this challenge, the clinical pathway (CP) is a useful model for managing the team's progress in providing health care services. High quality discharge planning for patients requires continuous refinement of CP including the collection and analysis of variance data, i.e., information not listed in the CP model. The purpose of this study is to analyze variance data gathered using PsychomsTM to find unidentified issues with keyword sorting (keyword variance analyses system) and text-mining (text mining variance analyses system). Using morphological analysis to detect word occurrences in variance data, it may be possible to identify problems needing solution by developing automatic rankings to analysis outcomes. To achieve this, however, specialized experience is required for variance analysis. Also, there must be high congruence between the results of text mining variance analyses and keyword variance analyses systems.
369.	Shunji Mitsuyoshi, Kouichi Shibasaki, Yasuto Tanaka, Makoto Kato, Tsutomu Murata, Tetsuto Minami, Haruko Yagura and Fuji Ren : Emotion Voice Analysis System Connected to the Human Brain, IEEE NLP-KE2007, 576-484, Beijing, Aug. 2007. (Summary) To investigate human brain activities in association with emotional speech, we developed a novel voice analysis system connected to a functional magnetic resonance imaging (fMRI) machine. Participants spoke inside the MR magnet during which BOLD activities of the brain was measured. Speech voice was transmitted through the newly developed mask-microphone inside the magnet to the external computer and was processed by the emotional voice analysis system. Two participants conversed without hindrance and their emotional state was analyzed. Using the system, we were able to detect brain activities during speech and simultaneously evaluate the human emotional voice. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2007.4368074 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2007.4368074 (DOI: 10.1109/NLPKE.2007.4368074)
370.	Zhi TENG, Fuji Ren and Shingo Kuroiwa : Emotion Recognition from Text based on the Rough Set Theory and the Support Vector Machines, IEEE NLP-KE2007, 36-41, Beijing, Aug. 2007. (Summary) In recent years, several methods on human emotion recognition have been published. But computer application on Chinese natural language processing (NLP) is still on the starting stage. In this paper, we proposed a scheme that emotion recognition from text through classification with the rough set theory and the support vector machines (SVMs). The basic steps are firstly to sample data sets, to build the decisions table, and to find importance of attributions and the simplest form of decisions table according to relative reduction and then the rough set model of system is obtained, finally train the predicting model by the SVMs. Our experiment results show that rough set theory and SVMs method are effective in emotion recognition, and the high recognition rate is resulted. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2007.4368008 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2007.4368008 (DOI: 10.1109/NLPKE.2007.4368008)
371.	Yun LI, Fang TIAN, Fuji Ren, Shingo Kuroiwa and Yixin ZHONG : A Method of Semantic Dictionary Construction from On-line Encyclopedia Classifications, IEEE NLP-KE2007, 82-89, Beijing, Aug. 2007. (Summary) This paper introduces a method of constructing a semantic dictionary automatically from the keywords and classify relations of the web encyclopedia Chinese WikiPedia. Semantic units, which are affixes (core/modifier) shared between many phrased-keywords, are selected using statistic method and string affix matching, also with other units to explain the semantic meanings. Then the result are used to mark the semantic explanations for most WikiPedia keywords by analyzing surface text or upper classes. The feature form ' structure or advantages comparing to other semantic resource are also concerned. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2007.4368015 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2007.4368015 (DOI: 10.1109/NLPKE.2007.4368015)
372.	Song LIU, Ye YANG, Fuji Ren and Shingo Kuroiwa : Questions Analysis of Confucius Analects Knowledge System, IEEE NLP-KE2007, 107-110, Beijing, Aug. 2007. (Summary) In this paper we explore the method based on keywords to analyze the questions for Confucius Analects Knowledge System. After analyzing the questions we can find the answers from the knowledge database of Confucius Analects. Confucius Analects Knowledge System is regard as a specific domain Question-Answer system. Taking a reference to the chapters' structure of Confucius Analects and the literature on Confucius Analects the chapters are classified into 8 categories. One of questions analysis' work is deciding the categories of questions. We use How Net to get all meanings of keywords then select congruent meanings for each category. Questions' categories depend on the keywords. All the questions collected are clustered by k-medoids algorithm. We find some rules from the clusters so that all the questions are classified into several types. The other work of questions analysis' is deciding the questions' types. Then we can find answers from the knowledge base. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2007.4368019 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2007.4368019 (DOI: 10.1109/NLPKE.2007.4368019)
373.	Manabu SASAYAMA, Fuji Ren and Shingo Kuroiwa : Automatic Super-Function Extraction for Translation of Spoken Dialogue, IEEE NLP-KE2007, 141-148, Beijing, Aug. 2007. (Summary) Extraction of a large number of super-function (SF) is the most important factor in realizing SF based machine translation. This paper presents a method for automatic extraction of SF from a Japanese-English bilingual corpus. The extraction process uses a bilingual dictionary to match Japanese and English nouns in each sentence pair. The experimental results using a Japanese-English bilingual corpus show that this method performs very well in automatically extracting SF for machine translation. In addition, we evaluate the extracted SF in SF based machine translation. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2007.4368025 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2007.4368025 (DOI: 10.1109/NLPKE.2007.4368025)
374.	Dapeng YIN, Peilin JIANG, Fuji Ren and Shingo Kuroiwa : Chinese complex long sentences processing method for Chinese-Japanese machine translation, IEEE NLP-KE2007, 170-175, Beijing, Aug. 2007. (Summary) The research on machine translation has been lasting for many years, and now this research field is increasingly a thoroughly refined. In practical machine translation system, the processing of a simple and short Chinese sentence has somewhat good results. However, but the complex long Chinese sentence translation still has difficulties. In this paper a new hierarchical approach processing for Chinese complex long sentence through analysis of Chinese punctuation, conjunctive words and syntax function is proposed. The method synthetically uses semantic characteristic of source Chinese sentence, which includes grammatical features, the length of the source sentence, punctuation and functional words. First phase is conjunctive words for simplified segmentation, and then the syntax analysis, in order to process complex long sentence by the multi-hierarchical approach. A long sentence is divided into several parts; every part gets the correct translation of the result separately, and then is combined by the comprehensive approach to gain the complex long sentence translation result. Experiments show that our approach can significantly reduce the time consumption and numbers of ambiguity, and also improve the accuracy and readability when parsing Chinese complex long sentence. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2007.4368029 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2007.4368029 (DOI: 10.1109/NLPKE.2007.4368029)
375.	Fang TIAN, Yun LI, Fuji Ren and Shingo Kuroiwa : Ontology based Domain Knowledge Construction, IEEE NLP-KE2007, 176-182, Beijing, Aug. 2007. (Summary) This paper presents a representation framework for domain knowledge based on the analysis of Chinese festival by ontology analysis approach; it also discusses the organization method for describing domain data based on ontology. At the same time, the paper summarizes the ontology study domain. It is conceptualized using method of domain knowledge by the framework, and that is to say, to construct the concept, the taxonomy of concept and the concept properties for the domain knowledge is based on ontology. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2007.4368030 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2007.4368030 (DOI: 10.1109/NLPKE.2007.4368030)
376.	BRACEWELL B. David, Fuji Ren, Katsutoshi HISAZUMI, Zhi TENG, Yuichi FUROSE and Shingo Kuroiwa : READING: A Self Sufficient Internet News System with Applications in Information and Knowledge Mining, IEEE NLP-KE2007, 190-196, Beijing, Aug. 2007. (Summary) This paper presents the READING (retrieving news around the world for discovery and knowledge mining) system, which is a self sufficient system for aggregating and classifying news from around the world with a focus on Asia. The system, however, goes beyond the traditional news aggregation sites by mining information and knowledge from the news articles to aid in such tasks as decision making. The system is able to collect, classify and mine knowledge automatically without the need for an editor or intervention by an administrator. Average users, news professionals and researchers alike will find that the system offers something for them. This paper focuses on the underlying algorithms in the system and how they interact in creating the overall system. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2007.4368032 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2007.4368032 (DOI: 10.1109/NLPKE.2007.4368032)
377.	Ye YANG, Song LIU, Shingo Kuroiwa and Fuji Ren : Question Answering System of Confucian Analects, IEEE NLP-KE2007, 361-366, Beijing, Aug. 2007. (Summary) This paper constructs a question answering system of Confucian Analects. As a result of context change and the difference of words' connotation between modern Chinese and ancient Chinese, the accuracy of content-based retrieval and category-based retrieval in the classical literature is quite low. In view of this, the paper has established the categories and pragmatics information base for Confucian Analects. It also proposes a retrieval method based on pragmatics information and categories. To increase accuracy and efficiency, the category keyword collection and the question type keyword table are established as well. When the system recognize the type and category of the user's question, it uses key word semantic matching. Namely, the category keyword collection and the question type keyword table are separately used to decide the category and the type. The experiments evidenced the effectiveness of answer extraction approach based on pragmatics information specific to in query with deep meaning. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2007.4368056 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2007.4368056 (DOI: 10.1109/NLPKE.2007.4368056)
378.	Junko Minato, Kazuyuki Matsumoto, Fuji Ren and Shingo Kuroiwa : Corpus Based Analysis of Japanese-English Emotional Expressions, IEEE NLP-KE2007, 413-418, Beijing, Aug. 2007. (Summary) Development of information technology has increased the chances of interaction between human and computer. Understanding not only semantic information but also underlying emotion will make communication with computer more natural and congenial. As preliminary research for emotion estimation from multilingual text, we focused on emotion expressions of Japanese and English and created a corpus with about 1,200 bilingual sentences and tagged emotions on words and sentences. Based on the corpus, we statistically analyzed the characteristics of how emotions were expressed in each language and also the relationships between sentence emotion and word emotion in the sentence. The results show the characteristics of emotion expressions in Japanese and English dialogue sentences. (Keyword) bilingual corpus / parallel corpus / emotion tagged corpus (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2007.4368064 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-47749090495 (DOI: 10.1109/NLPKE.2007.4368064, Elsevier: Scopus)
379.	Kyoko Osaka, Tetsuya Tanioka, Rozzano De Castro Locsin, Shu-ichi Ueno, Kazuyuki Matsumoto, Chiemi Kawanishi, Shingo Kuroiwa, Seiji Tsuchiya and Fuji Ren : Electroencephalograph Estimation Method of Measuring `Empathic Understanding', IEEE NLP-KE2007, 514-519, Beijing, Aug. 2007. (Summary) It is important for health care staff to understand patients' emotion and affective changes. Health care staffs should understand the patients' world as if this was his her own. This is called "empathic understanding". To understand the emotional process, electroencephalograph recording (EEG) was performed on five healthy participants while watching the sentimental movie which was 24-minutes long. The EEG changes during the emotional scenes were collected and compared with emotionally stable states. By using power map and spectrogram analyses of EEG, alpha bands at the occipital region were seen specifically among the emotionally impressed states. It seemed that the changes indicated the objective expression of empathic understanding. We suggest that EEG with power map and spectrogram analyses is a useful fundamental tool for developing a second generation computer system adjusted to the changes of one's mind. However, further examinations to remove artifacts among the EEG results are needed. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2007.4368080 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2007.4368080 (DOI: 10.1109/NLPKE.2007.4368080)
380.	Yamada Taichi, Seiji Tsuchiya, Shingo Kuroiwa and Fuji Ren : Classification of Facemarks Using N-gram, IEEE NLP-KE2007, 322-327, Beijing, Aug. 2007. (Summary) In this paper, we present an approach for the classification of facemarks into some facial expression categories. Facemarks are some of the expressions that are often used in text-based communication. Facemarks express human facial expression or action and they help us to understand what writers imply. However, there are some problems in the proccessing of the facemarks with computer; facemarks are numerous and users make new facemarks. Therefore, we propose to use the characters in facemarks to classify them. Though the facemarks are various, only some of signs and letters are used for the characters that compose the them. Moreover, there is a feature of the expressions of facemarks in the characters. We present an approach for facemarks classification using N-gram and evaluate this method. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2007.4368050 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2007.4368050 (DOI: 10.1109/NLPKE.2007.4368050)
381.	Shinomiya Mizuho, Fuji Ren, Shingo Kuroiwa and Seiji Tsuchiya : Extracting the Opinions of News Articles based on Emotionally Laden Words, IEEE NLP-KE2007, 262-267, Beijing, Aug. 2007. (Summary) In this paper we propose an approach to extract the opinion of the media from news articles based on emotionally laden words. In the propose approach, the opinions are judged by the total number of the emotion levels from articles. The emotion level is the number from -3 to +3 that indicate emotionally laden words whether have plus or minus images. The articles of baseball game and the editorial article are used as experiment object. The precision of the propose approach on the articles about baseball game is 66%, and on the articles of political event is 36%. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2007.4368041 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2007.4368041 (DOI: 10.1109/NLPKE.2007.4368041)
382.	Seiji Tsuchiya, Fuji Ren, Shingo Kuroiwa, Watabe Hirokazu and Kawaoka Tsukasa : A Semantic Information Retrieval Technique and an Evaluation for a Narrow Display Based on an Association Mechanism, IEEE NLP-KE2007, 209-214, Beijing, Aug. 2007. (Summary) The purpose of this study is to output information which users hope as high ranking results on narrow display of mobile information terminals. The concept of the proposed algorithm is to understand the meanings and the contents expressed by keywords and to retrieve appropriately related information. Concretely, we propose an information retrieval technique to evaluate the relationships between words using an association mechanism. A new test collection was made by 100 examinees who judged the retrieval results according to text meanings. Retrieval performance was objectively confirmed with the experiment based on the test collection. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2007.4368035 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1109/NLPKE.2007.4368035 (DOI: 10.1109/NLPKE.2007.4368035)
383.	Shingo Kuroiwa, Masashi Takashina, Satoru Tsuge and Fuji Ren : Artificial Bandwidth Extension for Speech Signals using Speech Recogniton, Proc. of INTERSPEECH 2007, 2501-2504, Antwerp, Belgium, Aug. 2007. (Keyword) speech recognition / speech recognition
384.	Lei Yu, Jia Ma, Fuji Ren and Shingo Kuroiwa : Automatic Text Summarization Based on Lexical Chains and Structural Features, Proceedings of 8th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, Vol.2, 574-578, Qingdao, China, Jul. 2007. (Summary) The rapid growth of the Internet has resulted in enormous amounts of information that has become more difficult to access efficiently. The primary goal of this research is to create an efficient tool that is able to summarize large documents automatically. We propose concept chains to link semantically-related concepts based on Hownet knowledge database to improve the performance of Text Summarization and suit Chinese text. Lexical chains is a technique for identifying semantically-related terms in text. The resulting concept chains are then used to identify candidate sentences useful for extraction. Moreover, the other method based on structural features which can makes the summary of the text have more general content and more balance is also proposed. The final experimental results proved the effectiveness of our methods. (Keyword) Text Summarization / Lexical Chains / HowNet
385.	Jiajun Yan, Bracewell B. David, Fuji Ren and Shingo Kuroiwa : Semi-Automatic Construction of an Emotion Ontology Using HowNet, Proceedings of the 2007 International Conference on Artificial Intelligence and Pattern Recognition, 17-21, FL, USA, Jul. 2007. (Summary) Emotion ontology construction is a desirable task in affective computing. In this paper, we propose to semi-automatically construct an emotion ontology using HowNet. First, an affective event hierarchy is extracted from HowNet's semantic event dictionary, which contains the semantic roles associated for each of the events. Next, three different types of tags are assigned to the semantic roles, of the predicates in the affective predicate hierarchy, creating an emotion predicate hierarchy. Then, a 120,496-words-scale knowledge dictionary is used to transform the emotion predicate hierarchy into an emotion ontology. In the end an ontology containing just under 5,500 verb concepts was created.
386.	Bracewell B. David, Fuji Ren and Shingo Kuroiwa : Low Cost Japanese-English Machine Translation for Cross-Lingual Information Retrieval, Proceedings of the 2007 International Conference on Artificial Intelligence and Pattern Recognition, 22-27, FL, USA, Jul. 2007. (Summary) In one form or another language translation is a necessary part of cross-lingual information retrieval systems. Often times this is accomplished using machine translation systems. However, machine translation systems offer low quality for their high costs. This paper proposes a machine translation method that is low cost while improving translation quality. This is done by utilizing multiple web based translation services to negate the high cost of translation. A best translation is chosen from the candidates using either consensus translation selection or statistical analysis. Which to use is determined by a heuristic rule that takes into account that most web based translation services are of similar quality and that machine translation still produces relatively poor results. By choosing the best translation the method is able to increase translation quality over the base systems, which is verified by the experimentation.
387.	Satoru Tsuge, Minoru Fukumi, Masami Shishibori, Fuji Ren, Kenji Kita and Shingo Kuroiwa : Study of Relationships Between Intra-Speaker's Speech Variability and Speech Recognition Performance, 2006 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS 2006), 41-44, Tottori, Japan, Dec. 2006. (Summary) Even if a speaker uses a speaker-dependent speech recognition system, speech recognition performance varies. For this reason, speech quality is varied by some factors, including emotion, background noise, and so on, even though the speaker and utterance remain constant. However, the relationships between intra-speaker's speech variability and speech recognition performance are not clear. Hence, we focus on the intra-speaker's speech variability which affects the speech recognition performances. To investigate these relationships, we have been collecting speech data since November 2002. Using a part of the speech corpus, we conducted speech recognition experiments. In this paper, we analyze the relationships between intra-speaker's speech variability and the phoneme accuracy by using the correlation analysis. For factors of the correlation analysis, we use a number of errors, a speaking rate, a likelihood. Analysis results show a strong correlation between the number of the substitution errors and the phoneme accuracy although the correlations of the number of the deletion and the insertion errors are low. Therefore, it is considered that there are overlaps between phonemes since the feature parameters vary at each speaking rate. For improving the phoneme accuracy, it is needed that we study a method which discriminates phonemes. On the other hand, although the correlation between the phoneme accuracy and the speaking rate seems to be low, a strong correlation between the speaking rate and the number of deletion errors and insertion errors are found. Since the number of the insertion errors and the number of the deletion errors were in the counterbalance relation, the correlation between the speaking rate and the phoneme accuracy was low. However, we consider that it is needed to normalize the speaking rate because the speaking rate influences on the number of the deletion and the insertion errors.
388.	Kyoko Osaka, Tetsuya Tanioka, Chiemi Kawanishi, Toshiko Tada, Rozzano De Castro Locsin, Shingo Kuroiwa and Fuji Ren : Measurement of the "emotional sensitivity" and "emotion at moment" using Power Map Analysis and Emotion Spectrum Analysis Method, Proceedings of International Symposium on Artificial Intelligence and Affective Computing 2006, 121-129, Tokushima, Nov. 2006. (Summary) The purpose of this study was to determine the emotional sensitivityof persons through empirical determination of electroencephalographic (EEG)data. With EEG electrodes in place, participants were requested to view anemotionally-charged video presentation.'Sensitivity at the moment' wasmeasured and found to be significantly changed, showing evidence ofemotional sensitivity at the point of occurrence. This change facilitates theunderstanding of caring emotion as openness to a formed intention of knowingthe other as caring person. Competencies in caring for persons are critical tounderstanding the valuing of technological competency as expression of caring.Technological competency as knowing others intentionally as 'sensitive beings'provided the impetus for the development of 'sensibility estimation technique'using brain wave activities to measure it.
389.	Xiaojie Wang and Fuji Ren : Constraint-based Chinese-Japanese Bitext Alignment, Proceedings of International Symposium on Artificial Intelligence and Affective Computing 2006, 1-12, Tokushima, Nov. 2006. (Summary) Bitext alignment is useful to many Natural Language Processing taskssuch as machine translation, bilingual lexicography and word sense disambiguation.This paper presents a Chinese-Japanese bitext alignment. After describing somecharacteristics in Chinese-Japanese bilingual texts, we first investigate somestatistical properties of Chinese-Japanese bilingual corpus, including the correlationtest of text lengths between two languages and the distribution test of length ratiodata. We then pay more attention to n-m(n>1 or m>1) alignment modes which areprone to mismatch. We propose a cross constrain measure based on Hanzi charactersinformation for these kinds of alignment modes. By using dynamic programming,we combine statistical information and Hanzi character information to find theoverall least cost in aligning. Experiments show our algorithm can achieve goodalignment accuracy. (Keyword) Alignment / Bitext
390.	Taichi Yamada, Fuji Ren and Shingo Kuroiwa : Classification of Facemarks Using Statistics of Characters, Proceedings of International Symposium on Artificial Intelligence and Affective Computing 2006, 175-182, Tokushima, Nov. 2006.
391.	Kenichi Mishina, Fuji Ren and Shingo Kuroiwa : An Emotion Similarity Calculation Using Dialog Sentence Corpora, Proceedings of International Symposium on Artificial Intelligence and Affective Computing 2006, 166-174, Tokushima, Nov. 2006. (Summary) In order to estimate an utterance persons emotion from asentence, a dictionary which assigned a emotion attribute for every wordis built, and, only as for which, there are many methods on based on sentencein which there is the word or not. However, there is a case wherethe emotion expressed by the word used simultaneously and word orderdiffers, plentifully. In this paper, in order to solve the above-mentionedproblem, we propose a method for an emotion similarity calculation thathow similar a dialog sentence is to which sentence betoken which emotions.This method defines a formula which calculates the similarity ofan input sentence and the dialog sentence classified according to emotoinbased on BLEU. The experiment calculates the rate which the emotionsare betokened by two dialog sentences became the same. These sentencesare the dialog sentence and the other dialog sentence which most similarto another. We call this rate emotion estimation success rate. The result,the emotion estimation success rate was improved more than onlyusing BLEU.
392.	Mayu Ymamoto, Fuji Ren and Shingo Kuroiwa : A Study on Automatic Emotion Tagging in Text Corpus, Proceedings of International Symposium on Artificial Intelligence and Affective Computing 2006, 183-191, Tokushima, Nov. 2006.
393.	Tomohiro Yagi, Fuji Ren and Shingo Kuroiwa : Speech Recognition for the Kanji Last Name Candidates Using Clarifying Information, Proceedings of International Symposium on Artificial Intelligence and Affective Computing 2006, 158-165, Tokushima, Nov. 2006.
394.	Jia Ma, Fuji Ren and Shingo Kuroiwa : Picture Processing in Expression Recognition, Proceedings of International Symposium on Artificial Intelligence and Affective Computing 2006, 147-157, Tokushima, Nov. 2006. (Summary) In recent years, along with the development of information technologyand artificial intelligence technology, the computers` human nature design hasgradually become possibly. In order to provide a better man-machine interactiveenvironment, we hoped the computer can understand and simulate humanity'sperceptual information. Being an important method for human to express thesentimental, the expression is a kind of direct-viewing and bright source material.Therefore, we hoped to establish a system, which enables the computer to recordand distinguishes humanity's expression, through some input devices like cameraand so on, thus to section peoples sentiment condition. In this article, we will dosome introduction and summary about the research work which has been carriedon, and then proposed some new research methods.
395.	Mizuho Shinomiya and Fuji Ren : Predicting the Emotion from News Articles based on Emotionally Laden Words and Classification of News Articles by Different Opinions, Proceedings of International Symposium on Artificial Intelligence and Affective Computing 2006, 192-200, Tokushima, Nov. 2006. (Summary) News about the same event can have radically different opinionsand emotions depending on the author, news paper company, andnationality. We assume that these opinions and emotions are related toeach other. In this paper we propose an approach to predict the emotionof news articles based on emotionally laden words, and to classify thenews articles using predicted emotions. The result of having attemptedto predict the emotions in the articles of baseball games and politicalevents, although the approach was effective in the articles of baseballgames, it was not effective in the articles of political events.
396.	Kazuyuki Matsumoto, Fuji Ren and Shingo Kuroiwa : An Emotion Estimation Method for Emotion Interface, Proceedings of International Symposium on Artificial Intelligence and Affective Computing 2006, 128-137, Tokushima, Nov. 2006. (Summary) The existing approaches of emotion estimation from a textwere mainly focused on estimating positive or negative emotions in thetext. However human emotions are more complex and we cannot judgeour emotions only by positive or negative. In this paper, we proposedan emotion estimation algorithm for conversation sentence. We gave therules of emotion occurrence to 1616 sentence patterns. In addition, we developeda dictionary which consisted of emotional words and emotionalidioms. The proposed method can estimate emotions in a sentence bymatching the sentence pattern of emotion occurrence and the rule. Furthermore,we can get two or more emotions included in the sentence bycalculating emotion parameter. We constructed the experiment systembased on the proposed method for evaluation. We analyzed weblog dataincluding 1645 sentences by the system, and conducted the experimentto evaluate emotion estimation accuracy. (Keyword) emotion interface / emotion estimation
397.	Jiajun Yan, Fuji Ren and Shingo Kuroiwa : Chinese Semantic Dependency Analysis and its Applications, Proceedings of International Symposium on Artificial Intelligence and Affective Computing 2006, 100-109, Tokushima, Nov. 2006. (Summary) Semantic analysis of natural language is a difficult but extremelydesirable task, because of its many uses. In this paper, an overviewof semantic dependency analysis and its applications are given. A decisiontree based semantic dependency analyzer for Chinese, which we callSEEN, is introduced. Then, an application of semantic dependency inAffective Computing is given. The application determines the emotionsof the actors in Chinese sentences.
398.	Manabu Sasayama, Fuji Ren and Shingo Kuroiwa : Evaluation of Super-Function based Japanese-English Machine translation, Proceedings of International Symposium on Artificial Intelligence and Affective Computing 2006, 89-99, Tokushima, Nov. 2006.
399.	Lei Yu, Fuji Ren and Shingo Kuroiwa : A Study on Automatic Text Summarization and News Collection, Proceedings of International Symposium on Artificial Intelligence and Affective Computing 2006, 81-88, Tokushima, Nov. 2006. (Summary) With the high speed growth of World Wide Web and on-lineinformation services, more and more information is available and accessible online.Meanwhile using mobile devices such as mobile telephone, PDA tobrowse through on-line information has become very popularly. But a largeamount of information and lengthiness information cant fit for the mobiledevices. In order to save this problem, we propose a method which collectsoriginal news text from on-line information and extracts summary from themautomatically. The system is made up by Automatic News Collection and AutoText Summarization. Our experimental results proved the effectiveness of themeans.
400.	Mohamed Abdel Fattah, Fuji Ren and Shingo Kuroiwa : Different Approaches for Bilingual Sentence Alignment, Proceedings of International Symposium on Artificial Intelligence and Affective Computing 2006, 70-80, Tokushima, Nov. 2006. (Summary) In this paper, we present new approaches to align sentences in bilingualparallel corpora based on the use of the linguistic information of the textpair in three different classifiers (feed forward neural network (FF-NNT), probabilisticneural network (P-NNT) and Gaussian mixture model (GMM)). A featureparameter vector is extracted from the text pair under consideration. Thisvector contains text features such as length, punctuate score, and cognate scorevalues. A set of manually prepared training data has been assigned to train oneof these classifiers. Another set of data was used for testing. Using the FF-NNT,P-NNT and GMM classifiers, we could achieve error reduction of 36%, 27%and 50% respectively over length based approach when applied on English-Arabic parallel documents.
401.	Yu Zhang, Fuji Ren and Shingo Kuroiwa : A Preliminary Research of Chinese Emotion Classification Model, Proceedings of International Symposium on Artificial Intelligence and Affective Computing 2006, 59-69, Tokushima, Nov. 2006. (Summary) There have been some studies about spoken natural language dialog, andmost of them have successfully been developed within the specified domains. However,current human-computer interfaces only get the data to process their programs.Aiming at developing an affective dialog system, we have been exploring how toincorporate emotional aspects of dialog into existing dialog processing techniques.As a preliminary step toward this goal, we work on making a Chinese emotion classificationmodel which is used to recognize the main affective attribute from a sentenceor a text. Finally we have done experiments to evaluate our model.
402.	David B. Bracewell, Fuji Ren and Shingo Kuroiwa : An Information Retrieval Library for Japanese and English News Articles, Proceedings of International Symposium on Artificial Intelligence and Affective Computing 2006, 47-58, Tokushima, Nov. 2006. (Summary) This paper presents a library of core algorithms for Japanese-English news-based cross-lingual information retrieval. The library isbroken up into three modules: Knowledge Acquisition, Knowledge In-terpretation and Knowledge Translation. This paper presents in detailone algorithm from each module. From the Knowledge Acquisition mod-ule, an algorithm for semi-automatically creating a special domain col-lection is presented. The algorithm is able to create good size documentcollections about a specific topic, person, etc. From the Knowledge In-terpretation module, an algorithm for extracting keywords from a singledocument that does not require a collection or corpus statistics is pre-sented. It is the basis for most of the algorithms in the library. Finally,from the Knowledge Translation module, an algorithm for choosing thebest translation of a text is presented. It uses a combination of statisticalanalysis and similarity measurement to choose the best translation froma set of candidates.
403.	Taichi Yamada, Fuji Ren and Shingo Kuroiwa : Classification of Facemarks Using Statistics of Characters, Proceedings of International Symposium on Artificial Intelligence and Affective Computing 2006, 2-9, Tokushima, Nov. 2006. (Summary) In this study, we present an approach for the classification of facemarks into some facial expression categories. Facemarks are some of the expressions that are often used in text-based comunication. Facemarks express human facial expression or action and they help us to understand what writers imply. However, there are some problems in the proccessing of the facemarks with computer; facemarks are numerous and users usually make new facemarks. Therefore, we propose to use the characters in facemarks to classify them. Though the facemarks are various, only some of signs and letters are used for the characters that compose the them. Moreover, there is a feature of the expressions of facemarks in the characters. We present an approach for the characters that compose the facemarks and evaluate a simple method for classification of facemarks by the characters. (Keyword) 顔文字 / 感性情報処理
404.	Takanori Hirai, Shingo Kuroiwa, Satoru Tsuge, Fuji Ren and Abdel Mohamed : A speech emphasis method for noise-robust speech recognition by using repetitive phrase, ICCT International Conference on Communication Technology (ICCT-06), 1269-1272, Guilin, China, Nov. 2006. (Summary) In this paper, we propose a novel noise-robust speech recognition technique using a repetitive phrase such as "Turn on the TV, Turn on the TV" as a speech command to control household appliance and on-vehicle apparatus. In daily conversation, the use of repetitive phrase with many syllable gives a low appearance ratio, and reduces the incorrect acceptance of a command. Moreover, speech emphasis may be expected by using repetitive phrase because each phrase is not influenced by unexpected noise at same time. In this paper, we propose to use repetitive phrase as speech emphasis. We conduct speech recognition experiment using the speech which are degraded by three kinds of noise: a buzzer, a whistle, and a telephone ring. From this experiment, we proposed method can improve the speech recognition accuracy under the condition of the all noises. Especially, the proposed method improves the speech recognition accuracy (from 25% to 86%) under the condition of the whistle noise. (Keyword) speech emphasis / speech recognition
405.	Takahiro Kuroda, Jia Ma, Fuji Ren and Shingo Kuroiwa : The Construction of The Facial Expression Video Database, ICCT International Conference on Communication Technology (ICCT-06), 1265-1268, Guilin, China, Nov. 2006. (Summary) In recent years, we pay attention to the facial expressions which can show the intentions of the speakers unconsciously, and we are trying to presuppose the emotions by using those expressions. In order to further the research, we need a great deal of expression data. However there is a little kinds of expression data and available in the research. Moreover those data are always in the picture type but not the video type that we want. Therefore, we built an facial expression video database in which a lot of expression data had been filled. This paper introduces the facial expression video database built by us. (Keyword) Facial expression / Video database / Emotion
406.	Masashi Takashina, Shingo Kuroiwa, Satoru Tsuge and Fuji Ren : Speech bandwidth extension method using speech recognition and speech synthesis, ICCT International Conference on Communication Technology (ICCT-06), 1273-1276, Guilin, China, Nov. 2006. (Summary) In this paper, we propose two kinds of novel speech bandwidth extension methods based on a speech recognition, a speech synthesis and a speech signal processing technique. In the proposed methods, the lost speech component by bandlimiting is generated with the technique of a speech recognition, a speech synthesis, and a speech signal processing by using the bandlimited speech information. For evaluating both proposed methods, we conducted the subjective and objective evaluation experiments. The experimental results shows the effectiveness of both proposed methods about the extension feeling of bandwidth. However, the evaluation of the speech quality became a not good result. Our problem is an improvement of the speech quality of the proposed method in the future. (Keyword) Bandwidth extension / Speech recognition / Speech synthesis
407.	Shingo Kuroiwa, Youji Mori, Satoru Tsuge, Masashi Takashina and Fuji Ren : Wind noise reduction method for speech recording using multiple noise templates and observed spectrum fine structure, ICCT International Conference on Communication Technology (ICCT-06), 1567-1571, Guilin, China, Nov. 2006. (Summary) Wind noise affects the quality of the speech recording in the field. In this paper, we propose a wind noise reduction method based on a signal processing technique. In the method, spectrum envelopes of wind noise are estimated by using referential multiple wind noise templates and the low freqency band spectrum envelope of the observed signal. Then, we estimate the noise spectrum using the estimated spectrum envelope and the fine structure of the observed signal. Finally, we subtract this estimated noise spectrum from the observed signal. For evaluating the proposed method, we conducted subjective and objective evaluation. The experimental results showed that the proposed method achieved much better improvement than conventional spectral subtraction. (Keyword) Wind noise reduction / Spectrum fine structure / Spectral envelope / Spectral subtraction
408.	Lei Yu, Mengge Liu, Fuji Ren and Shingo Kuroiwa : A Chinese Automatic Text Summarization system for mobile devices, The Pacific Asia Conference on Language, Information and Computation, 426-429, Wuhan, China, Nov. 2006. (Summary) A large amount of on-line information and lengthiness information can't fit for the mobile devices. In order to save this problem, we propose a method which collects original news text from on-line information and extracts summary sentences from them automatically. On this basis, we adopt WML(Wireless Markup Language) to build a news website for mobile devices browsing through the news summary. The system is mainly made up by Automatic News Collection and Auto Text Summarization. Our experimental results proved the effectiveness of the means. (Keyword) World Wide Web / Automatic Text Summarization / Automatic News Collection
409.	Fattah Abdel Mohamed, Fuji Ren and Shingo Kuroiwa : Machine Transliteration, The Pacific Asia Conference on Language, Information and Computation, 370-373, Wuhan, China, Nov. 2006. (Summary) In the present study, we present different approaches for transliteration proper noun pair's extraction from parallel corpora based on different similarity measures between the English and Romanized Arabic proper nouns under consideration. The strength of our new system is that it works well for low-frequency words. We evaluate the presented new approaches using an English- Arabic parallel corpus. Most of our results outperform previously published results in terms of precision, recall and F- Measure. (Keyword) Machine transliteration / Parallel corpora / Cross-language information retrieval
410.	Shingo Kuroiwa, Satoru Tsuge and Fuji Ren : Lost Speech Reconstruction Method using Speech Recognition based on Missing Feature Theory and HMM-based Speech Synthesis, Proc. of INTERSPEECH 2006, 1105-1108, Pittsburgh, Sep. 2006. (Summary) In recent years, IP telephone service has spread rapidly. However, an unavoidable problem of IP telephone service is deterioration of speech due to packet loss, which often occurs on wireless networks. To overcome this problem, we propose a novel lost speech reconstruction method using speech recognition based on Missing Feature Theory and HMM-based speech synthesis. The proposed method uses linguistic information and can deal with the lack of syllable units which conventional methods are unable to handle. We conducted subjective and objective evaluation experiments under speaker independent conditions. These results showed the effectiveness of the proposed method. Although there is a processing delay in the proposed method, we believe that this method will open up new applications for speech recognition and speech synthesis technology. (Keyword) speech recognition / speech recognition
411.	Kyoko Osaka, Kazuyuki Matumoto, Chiemi Kawanishi, Tetsuya Tanioka, Toshiko Tada, Shu-ichi Ueno, Rozzano De Castro Locsin and Fuji Ren : REQUIRED PRECISION TO NATURAL LANGUAGE PROCESSING FOR THERAPEUTIC PATIENT-HEALTH CARE PROVIDER COMMUNICATION, Proceedings of the 9th IASTED International Conference on Intelligent Systems and Control, 118-123, Honolulu,Hawaii,USA, Aug. 2006. (Summary) It is necessary to approach the caring humans perform by achieving empathetic understanding in human-robot communication and expressing caring feelings for a human-supporting robot. This paper aims at requiring precision to natural language processing for therapeutic patient-health care provider communication. First, our subjects were asked to view a video, which was to induce emotions. And then, an interview was carried out in order to identify the scenes that caused changes in the subjects' emotion. Also, the scenes were objectively judged by measuring the activity of an electroencephalogram (EEG) of the subjects. Finally, the lines of the scenes were extracted and, taking the subjects' impressions of their empathy as a criterion for judgement of natural language processing (NLP), compared with the analysis results by NLP. By our expe! riment, although it was difficult to make a judgment on the impressions in which emotions were intermingled such as joy and sorrow, NLP and the criterion for judgement that was the empathetic understanding of the subjects were consistent. It is clear that an empathetic understanding performed in medical welfare sites should be able to sensitively perceive pain, distress and loneliness of the subjects in particular. (Keyword) natural language processing / therapeutic communication / human support robot
412.	Yu Zhang, Fuji Ren and Shingo Kuroiwa : SEMI-AUTOMATIC EMOTION RECOGNITION FROM CHINESE TEXT, Proceedings of the 9th IASTED International Conference on Intelligent Systems and Control, 113-117, Honolulu,Hawaii,USA, Aug. 2006. (Summary) The interest in emotion recognition has attracted more and more attentions. There have been some studies about emotion extraction from spoken natural language dialog, and most of them have successfully been developed within the specified domains. But computer application on Chinese Natural Language Processing (NLP) is still on the starting stage. Aiming at developing a Chinese affective dialogue system, we have been exploring how to incorporate emotional aspects of dialogue into existing dialogue processing techniques. However, in Chinese linguistic corpora only few of them include emotional information. As a preliminary step toward this goal, we work on constructing what we call an emotion-thesaurus, as the base of our emotion recognition system. Then we construct the classification system using the thesaurus. Finally we give the evaluation of our system. (Keyword) Chinese affective dialogue system / emotional information / Chinese Natural Language Processing
413.	Jiajun Yan, Bracewell B. David, Fuji Ren and Shingo Kuroiwa : A Machine Learning Approach to Determine Semantic Dependency Structure in Chinese, Proceedings of the Nineteenth International Florida Artificial Intelligence Research Society Conference, 782-786, TL, USA, Aug. 2006.
414.	BRACEWELL B. David, Junko Minato, Fuji Ren and Shingo Kuroiwa : Determining the Emotion of News Articles, Lecture Notes in Computer Sciences, Vol.4114, 918-923, Germany, Aug. 2006. (Summary) Authors of news stories through their choice in words and phrasing inject an underlying emotion into their stories. A story about the same event or person can have radically different emotions depending on the author, newspaper, and nationality. In this paper we propose a system to judge the emotion of a news article based on emotion word, idiom and modifier dictionaries. This type of system allows one to judge the world opinion on varying topics by looking at the emotion used within news articles about the topic. (Link to Publication Site) ● Publication site (DOI): 10.1007/11816171_115 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1007/11816171_115 (DOI: 10.1007/11816171_115)
415.	Junko Minato, Bracewell B. David, Fuji Ren and Shingo Kuroiwa : Statistical Analysis of a Japanese Emotion Corpus for Natural Language Processing, Lecture Notes in Computer Sciences, Vol.4114, 924-928, Germany, Aug. 2006. (Summary) In this paper, we build a Japanese emotion corpus and perform statistical analysis on it. We manually entered in about 1,200 example dialogue sentences. We collected statistical information from the corpus to analyze the way emotion is expressed in Japanese dialogue. Such statistics should prove useful for dealing with emotion in natural language. We believe the collected statistics accurately describe emotion in Japanese dialogue. (Link to Publication Site) ● Publication site (DOI): 10.1007/978-3-540-37275-2_116 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1007/978-3-540-37275-2_116 (DOI: 10.1007/978-3-540-37275-2_116)
416.	Qiong Liu, Xin Lu, Fuji Ren and Akitoshi Mochizuki : A Hybrid Expert System for Stock Market Analysis - from Neural forecasting to Linguistic Expression, Proceedings of The Fourth International Conference on Information and The Fourth Irish Conference on the Mathematical Foundations of Computer Science and Information Technology, 144-147, Cork, Ireland, Aug. 2006.
417.	Bracewell B. David, Fuji Ren and Shingo Kuroiwa : Category Classification and Topic Discovery of News Articles, Proceedings of The Fourth International Conference on Information and The Fourth Irish Conference on the Mathematical Foundations of Computer Science and Information Technology, 345-348, Cork, Ireland, Aug. 2006.
418.	Manabu Sasayama, Fuji Ren and Shingo Kuroiwa : Automatic extraction of Super-Function from corpus and experimental evaluation, Proceedings of The Fourth International Conference on Information and The Fourth Irish Conference on the Mathematical Foundations of Computer Science and Information Technology, 395-398, Cork, Ireland, Aug. 2006.
419.	Kazuyuki Matsumoto, Tetsuya Tanioka, Fuji Ren, Yoichiro Takasaka, Takuya Matsuda, Toshiko Tada, Chiemi Kawanishi, Barnard Alan, Kyoko Osaka and Shu-ichi Ueno : Psychoms: A mental health patient management and variance analysis system using artificial intelligence, Proceedings of The Fourth International Conference on Information and The Fourth Irish Conference on the Mathematical Foundations of Computer Science and Information Technology, 73-77, Cork, Ireland, Aug. 2006. (Summary) Although it is agreed that there is a need for clinical pathway variance analysis, methods for creating a system are less well defined. The purpose of this paper is considering a way to develop the Psychoms that mental health patient management and variance analysis system using artificial intelligence. This system aims to improve a patient's quality of life through consistent and timely care and has potential to assist in the improvement of quality health care services. This article describes a method of outcomes management and variance analysis in this system and the prospective development of future research are discussed. (Keyword) Outcome management / variance analysis / nursing administration / team care / artificial intelligence
420.	Chiemi Kawanishi, Tetsuya Tanioka, Toshiko Tada, Fuji Ren, Kyoko Osaka, Kazuyuki Matsumoto, Shunji Mitsuyoshi, Rozzano De Castro Locsin and Shu-ichi Ueno : Consideration of Measuring Method for Empathic Understanding as Technological Competency of Nursing, Proceedings of The Fourth International Conference on Information and The Fourth Irish Conference on the Mathematical Foundations of Computer Science and Information Technology, 68-72, Cork, Ireland, Aug. 2006.
421.	Shuang Xiao, Hua Xiang, Fuji Ren and Shingo Kuroiwa : Chinese Idiomatic Expression Reading Support for Foreign Learners, Proceedings of The Fourth International Conference on Information and The Fourth Irish Conference on the Mathematical Foundations of Computer Science and Information Technology, 184-188, Cork, Ireland, Aug. 2006.
422.	Jiajun Yan, Bracewell B. David, Fuji Ren and Shingo Kuroiwa : Maximum Entropy Based Semantic Analysis of Chinese, Proceedings of The Fourth International Conference on Information and The Fourth Irish Conference on the Mathematical Foundations of Computer Science and Information Technology, 416-419, Cork, Ireland, Aug. 2006.
423.	Fuji Ren : Affective Information Processing and Recognizing Human Emotion, The Fourth International Conference on Information and The Fourth Irish Conference on the Mathematical Foundations of Computer Science and Information Technology, 11-22, Cork, Aug. 2006.
424.	Fattah Abdel Mohamed, Fuji Ren and Shingo Kuroiwa : PHONEME BASED SPEAKER MODELING TO IMPROVE SPEAKER IDENTIFICATION, ICGST International Conference on Artificial Intelligence and Machine Learning, 7-10, Sharm El Sheikh, Egypt, Jun. 2006. (Summary) The most common approach to speaker recognition today is the use of global Gaussian mixture models (GMM) which ignores knowledge of the underlying phonetic content of the speech, so it does not take advantage of all available information. In this paper we investigate the phoneme effect on speaker recognition system. We found that some phonemes have strong effect on speaker identification. By segmenting the most effective phonemes for speaker recognition task from a speaker utterance, we could decrease the system complexity and the recognition time. Moreover, this technique is very useful to speed up the authentication process through wire/wireless communication systems. This paper is concerned with improving the performance of speaker recognition systems in two areas: decreasing the identification error rate and decreasing the utterance part required for identification task. We have applied several approaches on YOHO corpus, most of these approaches were able outperform previously published results on the speaker identification task. One of our approaches could achieve 0.0% error rate using only an average segment of 13% of the testing utterance for recognition. (Keyword) phoneme effect / speaker recognition / knowledge
425.	Satoru Tsuge, Masami Shishibori, Kenji Kita, Fuji Ren and Shingo Kuroiwa : Study of Intra-Speaker's Speech Variability over Long and Short Time Periods for Speech Recognition, Proc. of 2006 IEEE International Conference on Acoustic, Speech, and Signal Processing (ICASSP2006), Vol.1, 397-400, Toulouse, France, May 2006. (Summary) In this paper, we describe a Japanese speech corpus collected for investigating the speech variability of a specific speaker over short and long time periods and then report the variability of speech recognition performance over short and long time periods. Although speakers use a speaker-dependent speech recognition system, it is known that speech recognition performance varies pending when the utterance was uttered. This is because speech quality varies by occasion even if the speaker and utterance remain constant. However, the relationships between intra-speaker speech variability and speech recognition performance are not clear. Hence, we have been collecting speech data to investigate these relationships since November 2002. In this paper, we introduce our speech corpus and report speech recognition experiments using our corpus. Experimental results show that the variability of recognition performance over different days is larger than variability of recognition performance within a day. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-33947625663 (Elsevier: Scopus)
426.	Jiajun Yan, Bracewell B. David, Fuji Ren and Shingo Kuroiwa : A Machine Learning Approach to Determine Semantic Dependency Structure in Chinese, Proceedings of the Nineteenth International Florida Artificial Intelligence Research Society Conference, 782-786, Melbourne Beach, Florida, USA, May 2006. (Summary) In this paper, we attempt to automatically annotate the Penn Chinese Treebank with semantic dependency structure. Initially a small portion of the Penn Chinese Treebank was manually annotated with headword and semantic dependency relations. An initial investigation is then done using a Naive Bayesian Classifier and some handcrafted rules. The results show that the algorithms and proposed approach are effective at determining semantic dependency structure automatically. The Naive Bayesian Classifier makes a good baseline algorithm for future research.
427.	Yoji Mori, Satoru Tsuge, Fuji Ren and Shingo Kuroiwa : Wind noise reduction method using the observed spectrum fine structure and estimated spectrum envelope, Proceedings of Nonlinear Circuits and Signal Processing (NCSP'06), 78-81, Honolulu, Mar. 2006. (Summary) In this paper, we propose a wind noise reduction method based on a signal processing technique. In this method, spectrum envelopes of wind noise are estimated by using referential multiple wind noise templates. Then, we estimate the noise spectrum using the estimated spectrum envelope and the fine structure of a observed signal. Finally, we subtract this estimated noise spectrum from the observed signal. For evaluating the proposed method, we conducted subjective and objective evaluation. The experimental results showed that the proposed method achieved much better improvement than conventional spectral subtraction. (Keyword) wind noise / noise reduction / speech enhancement
428.	Tetsuya Tanioka, Fuji Ren, Y Takasaka, Isao Nagamine and K Matumoto : Natural Language Processing Workshop, Beijing, Nov. 2005.
429.	Satoru Tsuge, Masami Shishibori, Fuji Ren, Kenji Kita and Shingo Kuroiwa : Data Collection for Investigating Speech Variability in a Specific Speaker Over Long and Short Time Periods, Proceedings of 2005 IEEE International Conference on Natural Language Processing and Knowledge Engineering (IEEE NLP-KE'05), 152-157, Wuhan, Oct. 2005. (Summary) In this paper, we describe a Japanese speech corpus collected for investigating the speech variability of a specific speaker over short and long time periods. Although speakers use a speaker-dependent speech recognition system, it is known that speech recognition performance varies pending when the utterance was uttered. This is because speech varies even if the speaker utters a specific sentence. However, the relationship between intra-speaker speech variability and speech recognition performance is not clear. We have not seen a corpus of Japanese speech data of a specific speaker over a long time period. Hence, since 2002, we have been collecting speech data for investigating the relationships between speech variability and speech recognition performance. In this paper, we introduce our speech corpus and conduct speech recognition experiments. Experimental results show that the variability of recognition performance over different days is larger than variability of recognition performance within a day. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2005.1598725 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-33847334792 (DOI: 10.1109/NLPKE.2005.1598725, Elsevier: Scopus)
430.	Hua Xiang, Peilin Jiang, Shuang Xiao, Fuji Ren and Shingo Kuroiwa : An Emotion Information Processing Model based on a Mental State Transition Network, Proceedings of 2005 IEEE International Conference on Natural Language Processing and Knowledge Engineering (IEEE NLP-KE'05), 668-673, Wuhan, Oct. 2005. (Summary) A machine that lacks of emotion computing ability cannot realize artificial intelligent sufficiently and cannot meet the increasing demanding of human-computer interaction as well. Though most current research is focusing on physical components of emotions, rarely are they carried out from the view of psychology. In this paper an Emotion Information Processing Model based on the Mental State Transition Network and a corpus of common sense [1] are proposed to detect human emotion. By a series of psychological experiments, we present a new way to predict future human's emotions depending on the various current emotional states under various conditions. Besides, people in different sexes characters and ages are taken into consideration in our experiments. From the psychological experiments data that is abstracted from 250 questionnaires, a Bayesian network for describing the transitions in distribution among the emotions and relationships between internal mental situations and external reinforcements are concluded. Further more comparing seven relative evaluating experiments we found that the model provided a higher precision average rate of 0.843 respectively for the 50 random data examples. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2005.1598820 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-33847280453 (DOI: 10.1109/NLPKE.2005.1598820, Elsevier: Scopus)
431.	Haiqing Hu, Peilin Jiang, Fuji Ren and Shingo Kuroiwa : Web-based Question Answering System for Restricted Domain Based of Integrating Method Using Semantic Information, Proceedings of 2005 IEEE International Conference on Natural Language Processing and Knowledge Engineering (IEEE NLP-KE'05), 529-534, Wuhan, Oct. 2005. (Summary) In this paper, we propose the construction of a webbased Question Answering(QA) system for restricted domain that combined three resource information databases for the retrieval mechanism, including a Question &Answer database, a special domain documents database and a web resource retrieved by Google search engine. We describe a new retrieval technique of integrating a probabilistic technique based on OkapiBM25 and a semantic analysis based on an ontology of HowNet knowledge base and a special domain HowNet created for the restricted domain. Furthermore, we provide a method of question expansion by computing word semantic similarity. The system is first developed for a middle-sized domain of sightseeing information. The experiments proved the efficiency of our method for restricted domain and it is feasible to transfer to other domains expediently using the proposed method. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2005.1598794 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-33847317426 (DOI: 10.1109/NLPKE.2005.1598794, Elsevier: Scopus)
432.	Mohamed Fattah, Fuji Ren and Shingo Kuroiwa : Sentence Alignment using Hybrid Model, Proceedings of 2005 IEEE International Conference on Natural Language Processing and Knowledge Engineering (IEEE NLP-KE'05), 388-392, Wuhan, Oct. 2005. (Summary) Parallel corpora have become an essential resource for work in multi lingual natural language processing. However, sentence aligned parallel corpora are more efficient than nonaligned parallel corpora for cross language information retrieval and machine translation applications. In this paper, we present a new approach to aligning sentences in bilingual parallel corpora based on the text character length between successive punctuates. A probabilistic score is assigned to each proposed correspondence of texts, based on the scaled difference of lengths of the two texts (in characters) and the variance of this difference. Using this score, the time required for punctuates matching decreased and the sentence alignment precision increased. Using this new approach, we could achieve 21.8% improvement over length based approach when applied on English-Arabic parallel documents. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2005.1598768 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-33847331618 (DOI: 10.1109/NLPKE.2005.1598768, Elsevier: Scopus)
433.	Shuang Xiao, Hua Xiang, Peilin Jiang, Fuji Ren and Shingo Kuroiwa : Chinese Conventional Expression Reading Support System for Japanese, Proceedings of 2005 IEEE International Conference on Natural Language Processing and Knowledge Engineering (IEEE NLP-KE'05), 232-237, Wuhan, Oct. 2005. (Summary) Understanding of Chinese conventional expression is a big difficulty for the Japanese readers who want to know the natures of Chinese language and culture properly. Though most current researches are focusing on Chinese reading support, there is still no perfect system that can provide a convenient supporting aiming at Chinese conventional expressions. In this paper a practical Chinese Conventional Expression Reading Support System is presented from the viewpoint of recognition science. And we have also created a Chinese Conventional Expression Database with 2305 conventional expressions of contemporary Chinese. At the same time we have analyzed the basic structures of these 2305 conventional expressions. By the analysis of the database we have classified three primary categories of these conventional expressions. Moreover, we have used the approach based on rules to recognize the Chinese conventional expressions. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2005.1598740 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-33847302446 (DOI: 10.1109/NLPKE.2005.1598740, Elsevier: Scopus)
434.	Kyoko Osaka, Shin-ichi Chiba, Tetsuya Tanioka, Chiemi Kawanishi, Isao Nagamine, Fuji Ren, Shingo Kuroiwa, Toshiko Tada, Ruriko Yamashita, Mayuko Kishimoto, Mika Nishimura, Ai Yamamoto, Rozzano Locsin and Yoichiro Takasaka : Estimating Emotion Changes Using Electroencephalographic Activities and its Clinical Application, Proceedings of 2005 IEEE International Conference on Natural Language Processing and Knowledge Engineering (IEEE NLP-KE'05), 830-834, Wuhan, Oct. 2005. (Summary) In the care, the communication based empathetic understanding is important. We have examined how to grasp empathetic understanding. We presume that the measurement of electroencephalographic (EEG) changes, those activities that are considered physiological indicators, enables an objective understanding of changes in emotions of those who have difficulty in expressing these through facial expression or physical action. Generally, EEG is used in the hospital to examine encephalopathy and brain disorder. Using an electroencephalograph device to acquire digital data we propose a method to objectively capture changes in the recognition state of people from changes in EEG activities (action potential), and a way to apply it into a clinical situation. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2005.1598851 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-33847291805 (DOI: 10.1109/NLPKE.2005.1598851, Elsevier: Scopus)
435.	Yu Zhang, Zhuoming Li, Fuji Ren and Shingo Kuroiwa : Semi-automatic Emotion Recognition from Textual Input Based on the Constructed Emotion Thesaurus, Proceedings of 2005 IEEE International Conference on Natural Language Processing and Knowledge Engineering (IEEE NLP-KE'05), 571-576, Wuhan, Oct. 2005. (Summary) After parsing an important task is to determine the semantic structure of sentences. In this paper, we attempt to automatically annotate the Penn Chinese Treebank with semantic dependency structure. Initially a small portion of the Penn Chinese Treebank was manually annotated with headword and dependency relations. Two supervised machine learning algorithms with varying features were then used to learn the relations. Finally, a set of rules were created based on features of Chinese to solve some problem patterns that were found in the Penn Chinese Treebank dealing with ambiguous structures. The experimental results show that the algorithms and proposed approach are effective for determining semantic dependency structure automatically. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2005.1598802 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-33847321536 (DOI: 10.1109/NLPKE.2005.1598802, Elsevier: Scopus)
436.	David Bracewell, Fuji Ren and Shingo Kuroiwa : Multilingual Single Document Keyword Extraction for Information Retrieval, Proceedings of 2005 IEEE International Conference on Natural Language Processing and Knowledge Engineering (IEEE NLP-KE'05), 517-522, Wuhan, Oct. 2005. (Summary) After parsing an important task is to determine the semantic structure of sentences. In this paper, we attempt to automatically annotate the Penn Chinese Treebank with semantic dependency structure. Initially a small portion of the Penn Chinese Treebank was manually annotated with headword and dependency relations. Two supervised machine learning algorithms with varying features were then used to learn the relations. Finally, a set of rules were created based on features of Chinese to solve some problem patterns that were found in the Penn Chinese Treebank dealing with ambiguous structures. The experimental results show that the algorithms and proposed approach are effective for determining semantic dependency structure automatically. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2005.1598792 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-33847285938 (DOI: 10.1109/NLPKE.2005.1598792, Elsevier: Scopus)
437.	Jiajun Yan, David Bracewell, Fuji Ren and Shingo Kuroiwa : Automatically Determining Semantic Relations in Chinese Sentences, Proceedings of 2005 IEEE International Conference on Natural Language Processing and Knowledge Engineering (IEEE NLP-KE'05), 262-267, Wuhan, Oct. 2005. (Summary) After parsing an important task is to determine the semantic structure of sentences. In this paper, we attempt to automatically annotate the Penn Chinese Treebank with semantic dependency structure. Initially a small portion of the Penn Chinese Treebank was manually annotated with headword and dependency relations. Two supervised machine learning algorithms with varying features were then used to learn the relations. Finally, a set of rules were created based on features of Chinese to solve some problem patterns that were found in the Penn Chinese Treebank dealing with ambiguous structures. The experimental results show that the algorithms and proposed approach are effective for determining semantic dependency structure automatically. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2005.1598745 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-33847259723 (DOI: 10.1109/NLPKE.2005.1598745, Elsevier: Scopus)
438.	Shingo Kuroiwa, Satoru Tsuge and Fuji Ren : A lost speech reconstruction method using linguistic information, Proceedings of 2005 IEEE International Conference on Natural Language Processing and Knowledge Engineering (IEEE NLP-KE'05), 126-130, Wuhan, Oct. 2005. (Summary) In recent years, IP telephone use has spread rapidly thanks to the development of VoIP (Voice over IP) technology. However, an unavoidable problem of the IP telephone is deterioration of speech due to packet loss, which often occurs on the wireless network. To overcome this problem, we propose a novel lost speech reconstruction method using speech recognition and synthesis. This proposed method uses linguistic information and can deal with the lack of syllable units which conventional methods are unable to handle. We conducted subjective and objective evaluation experiments. These results showed the effectiveness of the proposed method. Although there is a processing delay in the proposed method, we believe that this method will open up new applications for speech recognition and speech synthesis technology. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2005.1598720 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-33847311767 (DOI: 10.1109/NLPKE.2005.1598720, Elsevier: Scopus)
439.	Satoru Tsuge, Masami Shishibori, Fuji Ren, Kenji Kita and Shingo Kuroiwa : Frequency Characteristic Normalization Method using Blind Equalization Technique with Multiple References for DSR, Proceedings of 10th International Conference SPEECH and COMPUTER (SPECOM2005), Vol.1, 103-106, Patras, Greece, Oct. 2005. (Summary) In this paper, we propose a blind equalization method with multiple references for ETSI standard Distributed Speech Recognition (DSR) front-end. The proposed method compensates for acoustic mismatch caused by input devices. In ETSI advanced DSR front-end, the blind equalization method is introduced to compensate for acoustic mismatch. This method estimates the bias, which compensates for the mismatch, using one reference vector. If the input speech is short or contains many similar phonemes, there is concern that this method might not estimate the accurate bias. The proposed method estimates the bias using multiple references instead of one reference. Using multiple references, the proposed method estimates the bias more accurately. In addition, we represent the references by combining the VQ centroids used in the data compression process of ETSI standard DSR front-end. This limits increases in memory size and computation costs on the front-end. As a result, we can carry out this method in real-time on the DSR front-end. Experimental results on a Japanese newspaper dictation task indicate that the proposed method gave better performance under acoustic mismatched conditions than the conventional blind equalization method.
440.	Jianping Zhang, Fuji Ren and Tianyun Chen : Intelligent Tutoring Systems: Research Status and Its Development in China, Proceedings of IEEE International Conference on Natural Language Processing and Knowledge Engineering, Vol.2005, No.1, 683-689, Wuhan, China, Oct. 2005. (Summary) The first application of artificial intelligence (AI) to education has been to build intelligent tutoring systems (ITS). With the development of modern information technologies, ITS has been increasingly applied in education more and more widely. The applications of ITS in education have been changing the traditional instructional model and making learning more effective and meaningful. In this paper, the definition, architecture, and characteristics of ITS, some typical ITS and the current status, as well as its research focus of ITS are presented. Then the current research and applications of ITS in China are introduced. In the end, the paper discusses the future development of ITS. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2005.1598823 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-33748150694 (DOI: 10.1109/NLPKE.2005.1598823, Elsevier: Scopus)
441.	Shingo Kuroiwa, Yoshiyuki Umeda, Satoru Tsuge and Fuji Ren : Distributed Speaker Recognition using Speaker-Dependent VQ Codebook and Earth Mover's Distance, Proc. of INTERSPEECH 2005, Lisbon, Sep. 2005. (Summary) In this paper, we propose a distributed speaker recognition method using a non-parametric speaker model and Earth Mover's Distance (EMD). In distributed speaker recognition, the quantized feature vectors are sent to a server. The Gaussian mixture model (GMM), the traditional method used for speaker recognition, is trained using the maximum likelihood approach. However, it is difficult to fit continuous density functions to quantized data. To overcome this problem, the proposed method represents each speaker model with a speakerdependent VQ code histogram designed by registered feature vectors and directly calculates the distance between the histograms of speaker models and testing quantized feature vectors. To measure the distance between each speaker model and testing data, we use EMD which can calculate the distance between histograms with different bins. We conducted textindependent speaker identification experiments using the proposed method. Compared to results using the traditional GMM, the proposed method yielded relative error reductions of 85% for quantized data.
442.	Jiang Peilin, Hu Haiqing, Fuji Ren and Shingo Kuroiwa : Improved Semantic Similarity Computation in Question-Answering System, Proceedings of the Ninth IASTED International Conference on Artificial Intelligence and Soft Computing, Vol.2005, No.1, 429-433, Benidorm, Sep. 2005. (Summary) In this paper we propose an improved semantic similarity computation method for a Chinese question answering (QA) system [1]. The question answering system is capable to find out what answer are satisfy users requirements. Most successful QA systems aim at English. The conventional method used in Chinese QA systems for retrieving the related answers is Vector Space Model (VSM) in natural language processing (NLP). The VSM can only search by the keywords in the questions without the semantic relative information. The searching method in terns of semantic similarity considers not only the keywords but also the words related with keywords in semantics. We employ an improved method to use How net [2], a lexical knowledge base to calculate the word similarity and then the sentences similarity. The methods have been applied in our Japan Travel Question Answering System and the experiments are presented with satisfying results.
443.	Fuji Ren, Nobuo Nagano, David B. Bracewell, Shingo Kuroiwa, Tetsuya Tanioka, Zhong Zhang and Chengqing Zong : Facial Feature based Expression Recognition for an Affective Interface, Proceedings of the Ninth IASTED International Conference on Artificial Intelligence and Soft Computing, Vol.2005, No.1, 423-428, Benidorm, Sep. 2005. (Summary) We focus on human psychological characteristics to de velop general-purpose agents that can recognize human emotion and create machine emotion. In this paper a sys tem for identifying facial expressions by using facial fea tures is presented. The system recognizes 7 facial expres sions. The 7 facial expressions are made up of 6 basic emotional expressions (happiness, sadness, surprise, fear, anger, and dislike) and one non-expression. The Facial Ac tion Coding System (FACS) is used to make the resulting system robust. For identication, the shortest distance be tween the input features and features stored in a dictionary is used. From these facial expressions a users intention can be extrapolated and used to improve the human computer interaction experience.
444.	Shunji Mitsuyoshi and Fuji Ren : Language-independent Computer Emotion Recognition, Proceedings of the Ninth IASTED International Conference on Artificial Intelligence and Soft Computing, Vol.2005, No.1, 417-422, Benidorm, Sep. 2005.
445.	Tetsuya Tanioka, Isao Nagamine, Fuji Ren, Kazuyuki Matsumoto, Keisuku Ueta, Lei Yu, Yoichiro Takasaka, Toshiko Tada, Fumiko Hashimoto, Yasuko Matsushita and Ruriko Yamashita : Research on development of the Hospital Management Outcomes Analysis System for using in psychiatric hospitals, Proceedings of the Ninth IASTED International Conference on Artificial Intelligence and Soft Computing, Vol.2005, No.1, 434-438, Benidorm, Sep. 2005. (Summary) Recently, clinical pathways (CP) are often implemented to improve care, yet their effect on quality of care and outcomes have not been generally evaluated. Especially, the item of CP and the outcome management for the patient with mental disorders is not examined enough in Japan. The purpose of this paper is to examine the development of prototype Hospital Outcomes Analysis System (HOAS). As the first step of HOAS development, authors considered to create CP and outcome management item for people suffering schizophrenia for the improvement of quality mental health care. Comprehensive survey interviews were conducted for the hospital staff. CP for the patient with schizophrenic and the critical criteria for patient outcome management (OMCP) were developed from these surveys. Additionally, in order to fully utilize CP, it is very important to develop the efficient and effective means for managing patient outcomes. The CP and outcome management in the hospital may bring patients and their families in progress QOL, in addition to job satisfaction of care-givers. As the second step, we developed a prototype HOAS based on OMCP during the whole period from hospitalization to discharge of which patient outcomes management is done.
446.	Shinichi Chiba, Fuji Ren, Shingo Kuroiwa, Tetsuya Tanioka, Isao Nagamine, Chiemi Kawanishi, Toshiko Tada, Mayuko Kishimoto, Mika Nishimura, Ai Yamamoto, Kyoko Osaka and Hiroki Moriguchi : Analysis of electroencephalographic activity in condition of emotional activation in human, Proceedings of the Ninth IASTED International Conference on Artificial Intelligence and Soft Computing, Vol.2005, No.1, 445-450, Benidorm, Sep. 2005. (Summary) In the care, the communication based empathetic understanding is important. We have examined how to grasp empathetic understanding. As the first step, we study the characteristics of the electroencephalographic activity during subjects impressed time. We recorded electroencephalogram (EEG) of thirteen healthy female aged 19-29 years when the subjects were watching video. There were increases of the amplitudes of EEG during impressive scene of video. According to observation replayed EEG on display, as a result of analyzing two subjects' data among 13 persons, increase of amplitude was found firstly in Fp1, Fp2. Afterwards, increase of amplitude was gradually observed in F, O and T area. When healthy young females become impressed, the amplitude of their EEG increases. The more they are impressed, the more amplitude of their EEG increases.
447.	Fuji Ren, Jian Dianbing, Xiang Hua, Shingo Kuroiwa, Tetsuya Tanioka, Zhang Zhong and Zong Chengqing : Mental State Transtion Network and Psychological Experiments, Proceedings of the Ninth IASTED International Conference on Artifical Intelligence and Soft Computing, Vol.2005, No.1, 439-444, Benidorm, Sep. 2005. (Summary) Information recognition and extraction of human emotions from words and actions, facial expression and sensibil ity are necessary for machines in order to communicate smoothly with humans and to realize affective communica tion. We focus on human psychological characteristics to develop general-purpose agents that can recognize human emotions and create machine emotions. We comprehen sively analyze voice sounds and picture images that rep resent information included in emotion elements such as phonation, facial expressions, and language expressions. We analyze and estimate extensive statistical data based on the latest achievements of brain science and psychology in order to derive transition networks for human psycho logical states. We establish a speaker word model for the computer to simulate its own psychological transitions and emotional presentations, which is aimed to develop affec tive interface and establish theoretic structure and realiza tion method for emotion communication. In this paper, a Mental State Transition Network is presented and an affec tive interface based on the presented network is proposed, and some psychological experiments are given.
448.	Xiang Hua, Fuji Ren, Shingo Kuroiwa and Jiang Pelin : An Experimentation on Creating a Mental State Transition Network, IEEE International Conference on Information Acquisition, Vol.1, No.1, 432-436, Hong Kong, Jun. 2005. (Summary) Studies on the model of artificial psychology are the first step in the development of human-computer interaction. As affective computing remains unpredictable, creating a reasonable mental model becomes the primary task for building a hybrid system. A pragmatic mental model is also the fundament of some key topics such as recognition and synthesis of emotions. In this paper a Mental State Transition Network is presented and a psychological experiment based on the model is carried out. In this work, we hypothesize that internal mental movements of a human depend on a Mental State Transition Network that is made up of seven discrete emotional states. And we propose a new method to predict the emotional transitional probability distribution by using psychological questionnaires. The transition probability distribution of the model is calculated through a psychological experiment and the model provided a relatively high precision rate of 0.872 for the 50 random data examples used in a experimentation. (Keyword) mental State Transition Network / human emotion / psychological experiment (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-33947155276 (Elsevier: Scopus)
449.	Kazuyuki Matsumoto, Junko Minato, Fuji Ren and Shingo Kuroiwa : Estimating Human Emotions using Words and Sentence Patterns, IEEE International Conference on Information Acquisition, Vol.1, No.1, 421-426, Hong Kong, Jun. 2005. (Summary) Our research group proposes a method to recognize and create human emotions which can be applied to a robot used for welfare services. We also aim to develop an affective computer with enough ability to communicate that prople don't sense a disconnect. In this paper, an "emotion estimation module" based on words for recognizing human emotions. This mudule extracts "emotion occurrence condition" based on emotions contained in words and sentence meanings, and estimates the emotion of a speaker or writer. The meterials used for the module are collected from written quotations from conversations and internet blogs. We constructed a prototype system based on the proposed method and conducted an experiment on sentences taken from internet blogs in order to verify the effectivenss of the method. (Keyword) emotion recognition / human emotion / welfare service
450.	Yoshiyuki Umeda, Satoru Tsuge, Fuji Ren and Shingo Kuroiwa : Speaker Recognition using a Non-parametric Speaker Model Representation and Earth Mover's Distance, Proc. of International Workshop on statistical modeling approach for speech recognition, "BEYOND HMM", Kyoto, Dec. 2004. (Summary) In this paper, we propose a distributed speaker recognition method using a non-parametric speaker model and Earth Mover's Distance (EMD). In distributed speaker recognition, the quantized feature vectors are sent to a server. The Gaussian mixture model (GMM), the traditional method used for speaker recognition, is trained using the maximum likelihood approach. However, it is difficult to fit continuous density functions to quantized data. To overcome this problem, the proposed method represents each speaker model with a speaker-dependent VQ code histogram designed by registered feature vectors and directly calculates the distance between the histograms of speaker models and testing quantized feature vectors. To measure the distance between each speaker model and testing data, we use EMD which can calculate the distance between histograms with different bins. We conducted text-independent speaker identification experiments using the proposed method. Compared to results using the traditional GMM, the proposed method yielded relative error reductions of 32% for quantized data.
451.	Lin Ya, Tanihira Kokichi and Fuji Ren : An Interative e-Learning System Using Natural Language Processing Technology, Proceedings of the third International Conference on Information, 227-230, Tokyo, Nov. 2004. (Summary) In recent years, the remote education system using television and internet has been developed and applied not only in open universities and preparatory schools, but also in areas where educational resources are scarce. However, this system can not make response to the questions from students in real time. Therefore, we introduce a new interactive E-Learning system using natural language processing technology through which questions can be received and answered in real time.
452.	Ippei Fukuda, Mohamed Abdel Fattah, Satoru Tsuge, Fuji Ren and Shingo Kuroiwa : Robust Distributed Speaker Recognition to Solve the Differences in Frequency Characteristic Problem, Proceedings of the third International Conference on Information, 207-210, Tokyo, Nov. 2004. (Summary) Robust distributed speaker recognition to solve the differences in frequency characteristic problem Abstract:Recently data communication needs spread among wireless devices. However portable, wireless devices lack the memory and computational resources to handle medium and large, complex speech and speaker recognition systems. To overcome this problem, ETSI standard DSR front-end, running at client nodes, extracts the speech parameters, compresses them using split vector quantization and sends them to a remote server DSR back-end. However the VQ step for feature compression distorts the transmitted data which increases the speaker recognition error rate. In this paper, we conducted experiments for text independent speaker identification on a Japanese speech corpus. To decrease the effect of vector quantization distortion, we used the Bias Removal Method (BRM). BRM decreased the identification error rate by 16%.
453.	Yusuke Konishi, Fuji Ren and Shingo Kuroiwa : A Junior High School Science Education Support System Using Natural Language Processing Techniques, Proceedings of the third International Conference on Information, 235-238, Tokyo, Nov. 2004. (Summary) In this paper, a new method for constructing a junior high school science education support system using natural language processing technique is presented, and the outline of an experimental system based on the proposed method is described. In the system, the input sentence is analyzed and the science question sentences are generated automatically by using Super Function. The system can give more interesting questions and answers providing students pleasant learning environment. Moreover, the speech recognition and the voice synthesis are used for the system interface.
454.	Mohamed Abdel Fattah, Fuji Ren and Shingo Kuroiwa : Speaker Recognition for Mobile Communication Systems, Proceedings of the third International Conference on Information, 231-234, Tokyo, Nov. 2004. (Summary) Recently data communication spread to the mobile wireless world. The complexity of medium and large speech & speaker recognition systems are beyond the memory and computational resources of the small portable devices. Moreover the most common approach to speaker recognition today is the use of global Gaussian mixture models (GMM) which ignores knowledge of the underlying phonetic content of the speech, so it does not take advantage of all available information. In this paper we address the solution of these two problems by investigating the phoneme effect on speaker recognition system. We used YOHO database for speaker identification task. We found that some phonemes have strong effect on speaker identification. Segmenting the most effective phoneme for speaker recognition task from a speaker utterance and send this phoneme only through the wireless communication system will decrease the complexity of medium and speed up the authentication process though mobile communication system. We have applied different some approaches on YOHO corpus, several of these approaches were able outperform previously published results on the speaker ID task. One of our approaches could achieve 0.7% error rate by using only an average segment of 4.45% of the testing utterance for recognition.
455.	Zhenyu Jin, Fuji Ren and Shingo Kuroiwa : Chinese Korean Machine Translation System Using Super-Function, Proceedings of the third International Conference on Information, 223-226, Tokyo, Nov. 2004. (Summary) This paper describes how Super-Function Based Machine Translation (SFBMT) is used to translate original language (Chinese) sentences into the target language (Korean) sentences. SFBMT uses Super Function (SF) to translate without thorough syntactic and semantic analysis as most Machine Translation (MT) systems usually do. The SF is a function that shows the correspondence between original language sentence patterns and target language sentence patterns. Here, the proposed SFBMT Chinese-to-Korean is efficient in aiding human to browse documents written in Korean with Chinese indication.
456.	Qiong Liu, Fuji Ren and Shingo Kuroiwa : Natural Language Generation for Technical Analysis of Stock Market Using Extended Super-Function, Proceedings of the third International Conference on Information, 219-222, Tokyo, Nov. 2004. (Summary) In the last few years, neural network and other advanced methods have been used for the technical analysis of stock market. However, these methods have been very difficultly understood by non-expert users to improve their multivariate prediction ability for stock market. In this note, this paper discusses the usefulness of neural network model and other advanced methods for the technical analysis of stock market. The analytic results need to be expressed automatically in natural language for non-expert users. So this paper describes a natural language generation system based on extended super-function to express analysis information of stock market. This system is designed to collect a corpus of translation pairs between mathematic expression and language expression of technical analysis, then uses the extended super-function method to construct translation algorithm including comprehensive grammars and to generate the closest language expression.
457.	Kazuyuki Matsumoto, Fuji Ren and Shingo Kuroiwa : An Algorithm for Measuring Human Emotions based on Context and Sentence Pattern, Proceedings of the third International Conference on Information, 215-218, Tokyo, Nov. 2004. (Summary) It is necessary to nurse the senior citizen for declining population of children and increasing nuclear family. We are researching and developing a welfare robot which has a sensibility to support the life of the senior citizen and to reduce nursing. One of the basic researches on such welfare robots is to measure the sensibility from conversation sentences. In this paper, an algorithm for measuring the sensibility is presented, and a prototype system based on the proposed algorithm has been constructed.
458.	Manabu Sasayama, Fuji Ren and Shingo Kuroiwa : Super-Function based Japanese English Machine Translation Experiment and Evaluation, Proceedings of the third International Conference on Information, 195-198, Tokyo, Nov. 2004. (Summary) We present a new method called Super Function Based Machine Translation(SFBMT). SFBMT uses Super Function(SF) to translate without syntactic and semantic analysis as most conventional MT systems do. Using a SF, a translated sentence is fluent and translation speed is very fast. However, (1)The generality as a function is lost, because SF becomes longer as a sentence becomes long, (2)Specification of a candidate cannot be performed if SF has two or more candidates. In this paper, we experimented for the sentence which has extracted SF in order to investigate the cause of these two problems. As the experimental results, we proved that long SF can be divided into some short SF. Besides we proved that an English preposition and an English verb are changing with the attributes of a noun.
459.	Xin Zhao, Fuji Ren and Shingo Kuroiwa : A Super-Function Based Japanese Chinese Machine Translation System, Proceedings of the third International Conference on Information, 191-194, Tokyo, Nov. 2004. (Summary) Machine Translation (MT) tools are based on advanced computational linguistic analysis. MT ''engines'' linguistically process source documents to create a translation ''from scratch.'' In this paper, a Super-Function (SF) based Japanese-Chinese MT system is presented. The system uses the SF approach to do the translation without going through syntactic and semantic analysis as many MT systems usually do. The SF is a function that shows the correspondence between original language sentence patterns and target language sentence patterns. In this paper, we aim at performing MT between Japanese and Chinese to translate business letters by the SF based technique.
460.	Dapeng Yin, Fuji Ren and Shingo Kuroiwa : A method for processing Chinese ``BA'' sentence in Chinese Japanese machine translation system, Proceedings of the third International Conference on Information, 187-190, Tokyo, Nov. 2004. (Summary) There is a common but difficult problem in a Chinese-Japanese machine translation system, which is to process ``BA'' sentence. ``BA'' sentence is a sentence that has a prepositional word of ``BA''. Structural character of ``BA'' sentence is that the original verb is put behind the object word. The object word after preposition ``BA'' is used as an adverbial modifier of an active word. Nowadays, a practical Japanese-Chinese machine translation system based on translation rules has been developed. However, the current system is still unable to solve the problem when a complex ``BA'' sentence appears. This paper presents a method for processing Chinese ``BA'' sentence in Chinese-Japanese machine translation system. First of all, a large number of grammar items form Chinese grammar books are collected, some elementary judgment rules are set by classifying and inducing the collected grammar items. Then, these judgment rules are put into use in actual Chinese language and are modified by checking their results instantly. Rules are checked and modified by using the statistical information from an actual corpus. At the end, a five-segment model used for ``BA'' sentence translation is brought forward after above mentioned analysis.
461.	Haiqing Hu, Fuji Ren and Shingo Kuroiwa : Chinese Automatic Question Answwering System Based on Natural Language Feature and VSM, Proceedings of the third International Conference on Information, 183-186, Tokyo, Nov. 2004. (Summary) In this paper, we propose a question-answering construction, which synthesizes the answers retrieved to the questions most frequently asked, based on common knowledge and text knowledge about sightseeing information. In order to improve replies more accurately, one must consider the synthetic model based on statistic VSM and the shallow semantic analysis, so that the domain is only limited to sightseeing information. Lastly, the result is obtained by evaluation experiments, where high accuracy can be achieved when the results of retrieval are seen as correct, if the correct answer has appeared up to the third higher rank which sorts the value of the resembling degree. The experiments proved the efficiency in our method and it is feasible to use this method to develop Question-answering technology.
462.	Nobuo Nagano, Fuji Ren and Shingo Kuroiwa : Robust Recognition of Expression for Individual and Generality, Proceedings of the third International Conference on Information, 203-206, Tokyo, Nov. 2004. (Summary) To recognize face expression is very important issue in natural language understanding. In this paper, a new method for recognizing face expression, which consists of a preprocessing face expression image process, a detecting face area process, a extracting the characteristic process, and a recognizing the expression process, is presented. The recognized expressions in our research are seven kinds of expressionless, happy, surprise, disgust, fear, sadness and anger. In the method, for improving the system robustness, the face feature for each face expression is extracted by using FACS, and then they are compared with a face expression dictionary using a minimum distance method.
463.	Shingo Kuroiwa, Umeda Yoshiyuki, Satoru Tsuge and Fuji Ren : Histogram-based Speaker Recognition Method for Distributed Environment, Proceedings of the third International Conference on Information, 211-214, Tokyo, Nov. 2004. (Summary) In this paper, we focus on a distributed speaker recognition technique, in which quantized feature vectors are sent to a server, as with distributed speech recognition. The Gaussian mixture model (GMM), the traditional method used for speaker recognition, is trained using the maximum likelihood approach. However, it is difficult to fit continuous density functions to quantized data. To overcome this problem, we propose a novel non-parametric speaker recognition method based on histogram comparison. The proposed method calculates the distance between a histogram of registered quantized feature vectors and a histogram of testing quantized feature vectors. To measure distance, we use Earth Mover's Distance (EMD). The EMD has recently been successfully applied to image retrieval. We conducted text-independent speaker identification experiments using the proposed method. When compared to results using the traditional GMM, the proposed method yielded relative error reductions of 80% for quantized data.
464.	Satoru Tsuge, Shingo Kuroiwa, Masami Shishibori, Kenji Kita and Fuji Ren : Evaluation of frequency characteristic normalization method with multiple reference cepstrum on the Japanese newspaper article sentences speech corpus, Proceedings of the third International Conference on Information, 199-202, Tokyo, Nov. 2004. (Summary) 本論文では，分散型音声認識システムにおける入力系の周波数特性の違いによる音声認識精度の低下を抑制するため，複数の参照ケプストラムを用いた周波数特性正規化手法を提案した．提案手法は，フレーム同期で駆動し，各フレームで最近の参照ケプストラムを探し，周波数特性を正規化するバイアスを計算する手法である．提案手法の有効性を検証するため日本語連続音声認識実験を行った結果，提案手法は入力系の周波数特性が変動しても，音声認識精度の低下は少なく，有効であることがわかった．
465.	Zhang Zhong, Hisanaga Fujiwara and Fuji Ren : Image Processing Using 2-D Translation Invariant RI-Spline Wavelet, IEEE International Conference on System, Man & Cybernetics, 2971-2976, Netherlands, Oct. 2004. (Summary) We proposed a complex discrete wavelet transform (CDWT), which uses real-imaginary spline wavelet (RI-Spline wavwlet). In this study, we will extend the 1-D CDWT to the 2-D CDWT, which will be applied to image processing. The main results obtained can be summarized as follows: 1) The problem of 2-D translation variance which is caused by the DWT using a real mother wavelet. 2) The 2-D CDWT is applied to image processing, and encouraging results are obtained. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICSMC.2004.1400785 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-15744363244 (DOI: 10.1109/ICSMC.2004.1400785, Elsevier: Scopus)
466.	Zhang Zhong, Fujiwara Hisanaga and Fuji Ren : Signal Processing Using Translation Invariant RI-Spline Wavelet, IEEE International Conference on Systems, Man & Cybernetics, 3267-3272, The Hague, The Netherlands, Oct. 2004. (Summary) De-noising using wavelet shrinkage has a translation variance problem which we solve by using the translation invariant DWT. For this purpose, we propose a new complex wavelet, the real-imaginary spline wavelet. We also propose the Coherent Dual-Tree algorithm for the RI-Spline wavelet without increasing the computational cost very much. Then we apply this translation invariant RI-Spline wavelet for translation invariant denoising. Experimental results show that our method, when applied to ECG data and a music signal, can obtain better de-noising result than Wavelet Shrinkage. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICSMC.2004.1400844 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-15744396520 (DOI: 10.1109/ICSMC.2004.1400844, Elsevier: Scopus)
467.	Shingo Kuroiwa, Koji Tanaka, Satoru Tsuge and Fuji Ren : Acoustic model adaptation for coded speech using synthetic speech, Proc. of International Conference on Spoken Language Processing, Vol.4, 2925-2928, Cheju, Oct. 2004. (Summary) In this paper, we describe a novel acoustic model adaptation technique which generates speaker-independent HMM for the target environment. Recently, personal digital assistants like cellular phones are shifting to IP terminals. The encoding-decoding process utilized for transmitting over IP networks deteriorates the quality of speech data. This deterioration causes degradation in speech recognition performance. Acoustic model adaptations can improve recognition performance. However, the conventional adaptation methods usually require a large amount of adaptation data. The proposed method uses HMM-based speech synthesis to generate adaptation data from the acoustic model of HMM-based speech recognizer, and consequently does not require any speech data for adaptation. Experimental results on G.723.1 coded speech recognition show that the proposed method improves speech recognition performance. A relative word error rate reduction of approximately 12% was observed.
468.	Yoshiyuki Umeda, Satoru Tsuge, Fuji Ren and Shingo Kuroiwa : Distributed Speaker Recognition using Earth Mover's Distance, Proc. of International Conference on Spoken Language Processing, Vol.3, 2389-2493, Cheju, Oct. 2004. (Summary) In this paper, we focus on distributed speaker recognition, a technique in which quantized feature parameters are sent to a server, as with distributed speech recognition. The Gaussian mixture model , the traditional method used for speaker recognition, is trained using the maximum likelihood approach. The GMM has output probability functions with continuous density functions. It is difficult to fit continuous density functions to quantized data. To overcome this problem, we propose a novel speaker recognition technique which does not need estimation of statistical parameters. The proposed method directly calculates the distance between a set of quantized feature parameters of registered speech and a set of quantized feature parameters of test speech. To measure distance, we use Earth Mover's Distance (EMD). The EMD has recently been successfully applied to image retrieval. We conduct text-independent speaker identification experiments using the proposed method. When compared to results using the traditional GMM, the proposed method yielded relative error reductions of 75% (at 16kHz sampling) for quantized data.
469.	Zhao Xin, Fuji Ren and Vob Stefan : A Super-Function Based Japanese-Chinese Machine Translation System, 6th Conference of the Association for Machine Translation in the Americas, 272-281, Washington, DC, Sep. 2004. (Summary) In this paper, a Japanese-Chinese Machine Translation (MT) system using the so-called Super-Function (SF) approach is presented. A SF is a functional relation mapping sentences from one language to another. The core of the system uses the SF approach to translate without going through syntactic and semantic analysis as many MT systems usually do. Our work focuses on business users for whom MT often is a great help if they need an immediate idea of the content of texts like e-mail messages, reports, web pages, or business letters. In this paper, we aim at performing MT between Japanese and Chinese to translate business letters by the SF based technique.
470.	Kuniyoshi Kobayashi, Satoru Tsuge, Fuji Ren and Shingo Kuroiwa : A Packet Loss Concealment Algorithm using Speech Recognition and Synthesis, Proc. of the 18th International Congress on Acoustics, Vol.4, 3271-3274, Kyoto, Apr. 2004. (Summary) In recent years, IP telephone use has spread rapidly thanks to the development of VoIP (Voice over IP) technology. However, an unavoidable problem of the IP telephone is deterioration of speech due to packet loss, which often occurs on the wireless network. To conceal packet loss, modern codecs (e.g. G.711, G.723.1, G.729) derive the parameters for the lost frame from the parameters of previous frames. However, these methods cannot deal with losses more than 60 ms in length (in G.711), and cannot fundamentally deal with the loss of more than two phonemes. To overcome this problem, we propose a novel packet loss concealment algorithm using speech recognition and synthesis. First, using speech recognition based on Missing Feature Theory the phoneme-state sequence of the missing frames is presumed using acoustic information and linguistic information before and after the missing frames. Next, HMM-based speech synthesis generates a synthetic speech signal according to the presumed phoneme-state sequence to replace the missing data. The proposed method uses linguistic information and can deal with the lack of syllable units which conventional methods are unable to handle. We conducted subjective and objective evaluation experiments. For the subjective evaluation experiment, we conducted paired comparison auditory tests using 11 testees to examine the ease of understanding speech both lacking a section and having the synthesized replacement patch. Results show the proposed method improved perceived speech quality under all conditions. For the objective evaluation experiment, we measured speech quality using PESQ (ITU-T Recommendation P.862). The average PESQ value of the speech recovered by the proposed method was 3.37, while the value of the speech with a missing section was 2.78. Although there is a processing delay in the proposed method, we believe that the method will open up new applications for speech recognition and speech synthesis technology.
471.	Mohamed Fattah, Fuji Ren and Shingo Kuroiwa : Internet Archive as a Source of Bilingual Dictionary, Proc. of IEEE International Conference on Information Technology, Vol.2, 298-302, Apr. 2004. (Summary) Parallel corpus is a very important tool to construct a good machine translation system or make any natural language processing research for cross language information retrieval. Internet archive is a good source of parallel documents in different languages. In order to construct a good parallel corpus from the Internet archive, Bilingual dictionary that contains word pairs which may not exist in commercial dictionaries is a must. Extracting a bilingual dictionary from the internet parallel documents is important to add words that are absent from the traditional dictionaries. This paper describes two algorithms to automatically extract an English/ Arabic bilingual dictionary from parallel texts that exist in the Internet archive. The system should preferably be useful for many different language pairs. Like most of the systems done, the accuracy of our system is directly proportional to the amount of sentence pairs used. By controlling the system parameters, we could achieve 100% precision for the output bilingual dictionary, but the size of the dictionary will be smaller. (Link to Publication Site) ● Publication site (DOI): 10.1109/ITCC.2004.1286650 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-3042595845 (DOI: 10.1109/ITCC.2004.1286650, Elsevier: Scopus)
472.	Qiong Liu, Xin Lu, Fuji Ren and Shingo Kuroiwa : Automatic estimation of stock market forecasting and generating, Proc. of IEEE International Conference on Information Technology, Vol.1, 241-245, Apr. 2004. (Summary) Time-series forecasting is an important research area in several domains. Recently, neural networks have been very successfully applied in time series to improve multivariate prediction ability. Several neural network models have already been developed for the market prediction. Some are applied to predicting the change of future interest rate and exchange rate; some are applied to recognizing certain price patterns that are characteristic of future price changes. This paper presents a neural network model for technical analysis of stock market, and its application to a buying and selling timing prediction system for stock index of Japan. This paper also describes a natural language generation system to express prediction information of TOPIX in natural language for non-expert users. This system has evolved to be one of the most comprehensive grammars of English for prediction expressions. (Link to Publication Site) ● Publication site (DOI): 10.1306/09250303033 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-3042599590 (DOI: 10.1306/09250303033, Elsevier: Scopus)
473.	Fuji Ren : An Algorithm for Determining DingYu Structural using Grammar Knowledge, Fifth International Conference on Intelligent Text Processing and Computational Linguistics, 338-349, Seoul, Feb. 2004. (Summary) Current machine translation system lacks the ability for resolving the problem mentioned above. To resolve this problem, this paper presents an algorithm for determining DingYu structural particle using the grammar knowledge and statistical information. We first collect a large number of grammar items from Chinese grammar books, and obtain some elementary judgment rules by classifying and inducing the collected grammar items. Then we put these judgment rules into use in actual Chinese language, and modify the rules by checking their results instantly. Lastly we check and modify the rules by using the statistical information from a actual corpus. An experiment system based on the proposed algorithm has been constructed and an experiment is carried out. The result shows the effectiveness of the presented method.
474.	Mohamed Fattah, Fuji Ren, Shingo Kuroiwa and Alsayed Atlam : English/Arabic Bilingual Dictionary Construction using Parallel Texts from the Internet Archive, Proc. of the 46th IEEE International Midwest Symposium on Circuits and Systems, 253-256, Cairo, Egypt, Dec. 2003. (Summary) In order to construct a good machine translation system or make any natural language processing research for cross language information retrieval you must have a good parallel corpus. Internet archive contains a lot of parallel documents. To construct a good parallel corpus from the Internet archive, you must have a good bilingual dictionary. This paper describes an algorithm to automatically extract an English/ Arabic bilingual dictionary from parallel texts that exist in the Internet archive. The system should preferably be useful for many different language pairs. Unlike most of the systems done, our system can extract translation pairs from a very small parallel corpus. This new system can extract translations from only two sentences in one language and two sentences in the other language if the requirements of the system accomplished. Moreover, this system is able to extract word pairs that are translation of each other and the explanation of the Arabic or English word in the other language as well. The accuracy of the system is 59.1% in the case of one English word translated to one Arabic word, 23.9% in the case of one English word translated to more than one Arabic word (Arabic phrase), and 14.6% in the case of one Arabic word translated to more than one English word (English phrase).
475.	Mitsuyoshi Shunji, Fuji Ren, Lin Ya and Ogawa R. Joichi : Pragmatic Approach in Natural Language Understanding, IEEE International Conference on Natural Language Processing and Knowledge Engineering, Vol.1, 40-49, Beijing, Oct. 2003. (Summary) Natural languages that we use in daily conversation inevitably omit or insert various words. Incomplete sentences such as these may be grammatically correct, but they prevent machine translation systems from correctly interpreting such sentences as they assume meanings only from sentence-to-sentence context. This is largely due to the fact that context is a social product defined by the participants of a party, while translation machines literally translate the information provided by the speakers. The authors of this paper confirmed the effectiveness of syntactic constraint-lead approaches to Collaborative Fusion Machine Translation (CFMT) based on group Rorschach tests, in addition to semantic constraint-lead and syntactic constraint-lead machine translation processes. (Link to Publication Site) ● Publication site (DOI): 10.1109/NLPKE.2003.1275867 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-84945127303 (DOI: 10.1109/NLPKE.2003.1275867, Elsevier: Scopus)
476.	Fuji Ren, Matsumoto Kazuyuki, Mitsuyoshi Shunji, Shingo Kuroiwa and Lin Ya : Researches on the emotion measurement system, IEEE International Conference on System, Man & Cybernetics, 1666-1672, Washington, D.C., Oct. 2003. (Summary) In the near future, it will be necessary for the senior citizens to nurse the other senior citizens because of declining population of children and increasing a new type of family. We have been developing welfare robots which can support lives of the senior citizens and have sensibility to lighten the burden imposed on nursing. The measurement of emotions from the usual conversation is considered to be one of its basic researches. In the paper, we are going to propose the algorithm of the emotion measurement and the prototype system based on this algorism, and we are also going to discuss its validity. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-0242492033 (Elsevier: Scopus)
477.	Lin Ding, Zhou Yu, Zong Chengqing and Fuji Ren : Automatic Evaluation of Sentence Fluency, IEEE International Conference on System, Man & Cybernetics, 1687-1692, Washington, D.C., Oct. 2003. (Summary) In the machine translation (MT) system, how to evaluate the sentence fluency of the translation results is an important research topic. Most of the current methods are based on the similarity of output words compared with the reference translation, which don't specially address the evaluation of the sentence fluency according to the syntactic structure. This paper proposes a statistical approach to the problem, which is based on the n-gram language model and reference-independent. Our approach is a beneficial compensation to the reference-dependent methods and has better robustness than those methods based on the syntactic analysis. The preliminary experimental results indicate that the approach basically reflects the reality of human's judgment. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-0242576283 (Elsevier: Scopus)
478.	Li Taihao and Fuji Ren : Machine Translation method using super-function for Mobile Terminal, IEEE International Conference on System, Man & Cybernetics, 1693-1698, Washington, D.C., Oct. 2003. (Summary) The mobile telephone etc is the representation of mobile communication. In this paper we proposed a new machine translation method called Super-Function Based Machine Translation (SFBMT) to try to use for mobile terminal. SFBMT uses Super Function (SF) to translate the sentence without thorough syntactic and semantic analysis. And it can translate the sentence fast and high correct. Our experiment shows that this method can get 70% translation precision using the sentences that learned for extraction Super-Function, and 40% translation precision using the sentences that not learned for extracting Super-Function. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-0242408694 (Elsevier: Scopus)
479.	Shunji Mitsuyoshi and Fuji Ren : The Sensibility Inference Function by Psycho-Quantum Computer, IEEE International Conference on System, Man & Cybernetics, Vol.2, 1679-1686, Washington, D.C., Oct. 2003. (Summary) Human cognition stems from his identifying the relation or relative distance between himself and any other objects or persons, for which prerequisite is establishing his `self'. In other words, it is presumable that the potential of intelligent machine's establishing its `self' would require us to engineer its sense of `ego' and `intention', which involves such factors as `emotions', `instincts', and `sensibilities'. This dissertation introduces the psycho-quantum theory which illustrates the human psychodynamics by the quantum mechanics approach, and its application for constructing the distribution model of emotional modalities and the autonomous system, the essential elements for creating an ego in a computer. We have attempted to create the artificial `ego' and `desire' based on our probability model and state transition analysis, then accordingly developed our methodology of the artificial thought process as well as the judging mechanism of such computer. Furthermore, this dissertation introduces the sensibility inference function of our psycho-quantum computer, by which we discuss our methods to itemize 126emotional modalities of human, construct the three-dimensional dynamic model of emotions, and analyze the emotion distribution and its longitudinal modal transition so as to derive the artificial instinct and to determine/infer its relationship with external factors. Currently, our technology to construct the comprehensive psycho-quantum computer is yet in developmental stage; however, its potential is enormous so that it will constitute a key technology in new robotics industry. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-0242576282 (Elsevier: Scopus)
480.	Shingo Kuroiwa, Satoru Tsuge and Fuji Ren : Blind equalization via minimization of VQ distortion for ETSI standard DSR front-end, Proceedings of Natural Language Processing and Knowledge Engineering, Vol.1, 585-590, Beijing, Oct. 2003. (Summary) In this study we present blind equalization techniques for ETSI standard Distributed Speech Recognition (DSR) front-end which compensate for acoustic mismatch caused by input devices. The DSR front-end employs vector quantization (VQ) for feature parameter compression so that the mismatch does not only cause a shift of parameters but also increases VQ distortion. Although CMS is one of the most effective methods to compensate for the shift, it can not decrease VQ distortion in DSR. To compensate for the shift and decrease VQ distortion simultaneously, the proposed methods estimate the shift in the input data necessary to match the VQ codebook distribution. The methods do not need the acoustic likelihood which is calculated in a decoder on the server side. Therefore, they are applicable to the DSR front-end. Japanese Newspaper Article Sentences database (JNAS) was used for the equalization experiments. While the word error rate (WER) for ETSI standard DSR front-end was 18.6% under acoustic mismatched condition, our propsed method yielded a rate of 12.3%.
481.	Manabu Sasayama, Fuji Ren and Shingo Kuroiwa : Super-Function based Japanese-English machine translation, Proceedings of Natural Language Processing and Knowledge Engineering, Vol.1, 555-560, Beijing, Oct. 2003. (Summary) We have presented a new method called Super-Function Based Machine Translation (SFBMT). SFBMT uses Super-Function (SF) to translate without syntactic and semantic analysis as most conventional MT systems do. SF represents correspondence with a source language sentence structure and a target language sentence structure directory. According to this feature, the system realizes very fast translation. Moreover we do not feel the sense of incompatibility in the translation result because the SFs are automatically generate from a large corpus. In this paper, we describe (1) SF based machine translation, (2) extracting SF, (3) the evaluation experiment. As the experimental results, we obtain 84% of effective rates of translation.
482.	Koji Tanaka, Shingo Kuroiwa, Satoru Tsuge and Fuji Ren : An acoustic model adaptation using HMM-based speech synthesis, Proceedings of Natural Language Processing and Knowledge Engineering, Vol.1, 368-373, Beijing, Oct. 2003. (Summary) Recently, personal digital assistants like cellular phones are shifting to the IP terminal. The encoding-decoding process utilized for transmitting over IP networks deteriorates the quality of the speech data. This deterioration causes degradation in speech recognition performance. Acoustic model adaptations could improve recognition performance. However, the current adaptation methods usually require a large amount of adaptation data. A novel adaptation method using speech synthesis based on HMM (Hidden Markov Model) is proposed. This method does not require speech data for adaptation because speech data is generated by speech synthesis from the acoustic model. Experimental results on G.723.1 coded speech recognition show that the proposed method improves speech recognition performance.
483.	Smith B. Arthur, Shi Hongchi and Fuji Ren : An XML-based Platform-Independent Model-Level Interface fro Database Applications, IEEE International Conference on Systems, Man and Cybernetics, Tunisia, Oct. 2002. (Summary) In this paper, we present a platform-independent model-level interface for database applications. This is an XML-based meta-protocol which, when combined with application-specific metadata, produces a protocol that supports complete interaction with a database. Specification of the metadata at the data modeling level eliminates any dependence on the nature of the underlying database platform. This paper focuses on the database query and response elements of the protocol.
484.	Li Taihao, Fuji Ren, Shingo Kuroiwa and Kenji Kita : To define the feature function in extracting Japanese-Chinese bilingual word pairs using maximum entropy modeling, IEEE International Conference on Systems, Man and Cybernetics, Vol.3, 291-294, Tunisia, Oct. 2002. (Summary) In this paper, we present an approach to construct a translation dictionary used in multilingual natural language processing such as machine translation. We use a learning and extracting method of bilingual word pairs from parallel corpora using the maximum entropy modeling. We have conducted the experiments in Japanese and Chinese parallel corpora. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-0038345949 (Elsevier: Scopus)
485.	Fuji Ren and Mituyoshi Shunji : Machine-Aided Writing Function in MMM Intelligent System, IEEE International Conference on Systems, Man and Cybernetics, Tunisia, Oct. 2002. (Summary) Multi-lingual Multi-function Multi-media intelligent system (MMM) is a big project, it is a complex intelligent system with multiple functions that can deal with multiple languages and multiple media. We have designed a new general ontology based natural language processing system referred to as Multi-lingual Multi-functions Multi-media Intelligent System. In this paper, we describes a new function, Machine-Aided Writing Functions, in the MMM system. Our methodology proposed in this paper can deal with any foreign languages, but we only focus on how to construct a Machine-Aided English Writing system for Japanese users in the paper. With the rapid development of the internet, writing English becomes daily work for computer users all over the world. However, for most non-native users not only on spelling checking and grammar checking but also on writing native sentences using the expression way of native-English is a challenging task. The basic idea of the method proposed in this paper is based on Super-Function (SF) means and Corpora Intelligence Technique (CIT). SF is a new concept that we presented to develop multi-lingual machine translation. A prototype Machine Translation Aiding English Writing system has been constructed based on the proposed method. Some experiments using the prototype system have been carried out and the results show the proposed method is effective. In this paper we will discuss the SF and CIT in detail and give some new advance in MMM project.
486.	Fuji Ren, Li Shigang, Shi Hongchi and Shingo Kuroiwa : Semi-Automatic Acquisition Translation Knowledge from Parallel Corpora, IEEE International Conference on Systems, Man and Cybernetics, Vol.3, 279-284, Tunisia, Oct. 2002. (Summary) Translation in most current machine translation systems is based on rules. a crucial problem in such rule-based machine translation is how to acquiring the translation knowledge, or called translation rules. many studies have been conducted for automatic acquisition in the past, but they require a great deal of annotated examples. however, it is difficult to get a large number of the annotated examples. at fact, most bilingual texts are not matched in sentences, although matched as the whole text. in this paper, we describe a semi-automatic process of acquisition machine translation knowledge from japanese-chinese parallel corpora. the process consists of the following three parts. the first part is parallel text alignment, pta for short. the second part is example analysis and annotation, eaa for short. and the third part is construction of the translation rules, ctr for short. the process interacts with a linguist in order to solve problems that the system is unable to solve. this approach is more efficient than the completely automatic approach in the sense that fewer examples are required. in this paper, we describe the basic idea and the methods of pta, eaa, and ctr. a prototype system based on the proposed method has been built and some experiments on japanese- chinese have been carried. the results show that once the acquired knowledge is integrated with an mt system, we observe a signicant improvement in translation quality. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-0038345956 (Elsevier: Scopus)
487.	Mituyoshi Shunji and Fuji Ren : Sentience System Computer: Principles and Practices, IEEE International Conference on Systems, Man and Cybernetics, Vol.4, 557-564, Tunisia, Oct. 2002. (Summary) Research on artificial intelligence and sensitivity control technology progresses in recent years, and the technology of imitation human thinking, feeling, and sensitivity have been established. However, research on Sentience as the way of idea generation and intuition that are the origin of human being's intellectual production activity seems to have just started. Moreover, although the field of quantum computer is also being researched briskly, no practical results have been produced yet. In this paper, a new machine called Sentience System Computer (SSC) is presented. SSC is an intuition computer system having self-intention. According to the interpretation in the many-words quantum theory, the spontaneous intuition of human can be defined as what is produced by interference from the self multiple worlds which are resulted from all piles of self-history. In this paper, we present the principles and practices of SSC, the basic spontaneity type algorithm. When applying SSC to sensitivity control technique, the process of generating sentience, the procedure of human conceives, the state of Idea Database and some recent results of SSC, are given also. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-0036970115 (Elsevier: Scopus)
488.	Tai Xiaoying, Fuji Ren and Kenji Kita : Long-term Relevance Feedback using Simple PCA and Linear Transformation, 13th International conference and workshop on Database and Expert Systems Applications, 261-265, France, Sep. 2002. (Summary) This paper proposes a new method to improve information retrieval performance of the vector space model by preserving user-supplied relevance information for a long term in the system.
489.	Satoru Tsuge, Shingo Kuroiwa, Masami Shishibori, Fuji Ren and Kenji Kita : Robust Feature Extraction in a Variety of Input Devices on the Basis of ETSI Standard DSR Front-end, 7th International Conference on Spoken Language Processing, 2221-2224, Denver, USA, Sep. 2002. (Summary) This paper reports an evaluation ETSI standard DSR (Distributed Speech Recognition) front-end through continuous word recognition on a Japanese speech corpus and proposes a method, the basis removal method, that reduces the distortion between feature vector and VQ codebook.
490.	Zhou Qiang, Drabek France Elliott and Fuji Ren : Annotating the functional chunks in Chinese sentences, In Proceedings of the Third International Conference on Language Resources and Evaluation, 731-738, Las Palmas de Gran Canaria, Spain, Aug. 2002. (Summary) The paper proposed a new syntactic annotation scheme functional chunk, which tried to represent information about grammatical relations between sentence-level predicates and their arguments. Under this scheme, we built a Chinese chunk bank with about two million Chinese characters, and developed some learned models for automatically annotating fresh text with functional chunks. We also proposed a two-stages approach to build Chinese tree bank on the top of chunk bank, and gave some experimental results of chunk-based syntactic parser to show the advantage of functional chunk for parsing performance increase. All these work lays good foundations for further research project to build a large scale Chinese tree bank.
491.	Fuji Ren and Shunji Mitsuyoshi : The Ideal Computer: Understanding and Creating the Emotion and Sensitivity, Proceedings of China-Japan Joint Symposium on Science and Technology in the 21st Century, 62-68, Beijing, Jul. 2002. (Summary) On the basis of considering Sentience as a concrete algorithm and equipment, we have conducted the research on the principle of the many-worlds interpretation for the quantum theory of astrophysics. In this paper, a new machine called Sentience System Computer (SSC) is presented. SSC is an intuition the interpretation in the many-worlds quantum theory, the spontaneous intuition of human can be defined as what is produced by interference from the self multiple worlds which are resulted from all piles of self-history. If the total of the interferences from the multiple worlds other than human self is already fixed (based on the law of mass preservation, and the law of energy preservation), it will be possible to control the interferences. Consequently, the basic concept of SSC is drawn from the idea that the cause of the way of thinking of a machine and intuition in SSC become reproducible by the quantum theory-algorithm. We present the principles and practices of SSC, the basic spontaneity type algorithm. When applying SSC to sensitivity control technique, the process of generating sentience, the procedure of human conceives, the state of Idea Database and some recent results of SSC , are given also.
492.	Xin Zhao, Fuji Ren, Shingo Kuroiwa and Manabu Sasayama : Japanese-Chinese Machine Translation System Using SFBMT, International Conference on Information-2002, Series of Information & Management Sciences, Vol.3, 16-21, Beijing, Jul. 2002. (Summary) Information circulation between international has come to be frequently performed with social high advancement in information technology, and the necessity for machine translation has been increasing quickly. In fact most users prefer that the system is fast, inexpensive, easy to control and easy to update. This means that we don't need high fluency of the translations but a useful translation system. In recent years, in order to realize a highly precise machine translation system, many machine translation systems have been put in practical use. Such conventional research aims at raise the accuracy and fluency of a translation sentence but there are many problems. In this paper, a Japanese-Chinese machine translation method using Super-Function (SFBMT) is presented. SFBMT uses Super-Function to translate without through syntactic and semantic analysis at most MT systems usually do. The SF is a function that shows the correspondence between original language sentence and target language sentence. In this paper, we aim to perform the Machine Translation between Japanese and Chinese by the technique.
493.	Minoru Nagayasu, Fuji Ren and Shingo Kuroiwa : Machine-Aided English Writing Prototype System, International Conference on Information-2002, Series of Information & Management Sciences, Vol.3, 22-26, Beijing, Jul. 2002. (Summary) The chance to make the writing English increases by the internationalization. However, writing English is a big barrier for most Japanese users. The machine translation is enumerated as typical support method of the writing English. It is possible in a large amount of translation short time. However, the machine translation cannot translate any sentences, and it is difficult to generate native-English. In this paper, we propose an approach to Writing English support system for Japanese users. The approach is based on examples. The example presentation type consists of two components: 1) Support by English sentence classification, and 2) Support by use of Super-Function. Both components work together in a unified way and improve the quality of presentation examples. We also developed English writing support tool of prototype. The writing English support system was evaluated with this tool, and it worked on the system development.
494.	Tomoyuki Kagawa, Fuji Ren and Shingo Kuroiwa : Automatic Map-Generation Based on Verb Frames, International Conference on Information-2002, Series of Information & Management Sciences, Vol.3, 107-112, Beijing, Jul. 2002. (Summary) In this paper, we present a method to generate a map from natural language. First of all, to generate the guide map, the guide sentence was divided into named ``Guidance Unit''. It is fundamental division unit punctuated with each morpheme that is independence verb. By using this unit, irrelevant expressions can be excluded from the analysis, and also more flexible expressions can be taken into account. Next, after the guidance unit had been made verb frames, spatial information was extracted. After that, the guide map was generated based on proposed method has been built and some experiments have been carried out. The experimental result shows the effectiveness of the proposed methods.
495.	Manabu Sasayama, Fuji Ren, Shingo Kuroiwa and Zhao Xin : Japanese-English Machine Translation Systems for Web Users Using Super-Function, International Conference on Information-2002, Series of Information & Management Sciences, Vol.3, 366-371, Beijing, Jul. 2002. (Summary) We have presented a new method called Super-Function Based Machine Translation (SFBMT). SFBMT uses Super-Function (SF) to translate without thorough syntactic and semantic analysis as most MT systems do. This translation speed is very fast. And more we do not feel the sense of incompatibility in the translation result because SF is a corpus base. For a fact use of the Internet increases, more and more necessary information is often written in foreign languages. Web user hopes fast translation and easy control systems. SFBMT is best for their hopes.
496.	Kouji Tanaka, Shingo Kuroiwa, Satoru Tsuge and Fuji Ren : The Influence of Speech Coders for IP telephone on Speech Recognition Performance, International Conference on Information-2002, Series of Information & Management Sciences, Vol.3, 44-48, Beijing, Jul. 2002. (Summary) For transmission over IP networks, speech must be encoded at the sending end and subsequently decoded at the receiving end. In this encoding-decoding process, some speech information has to be removed and it is natural that the performance of speech recognition systems will deteriorate when the coded speech is applied as input to a recognition system. This paper reports an evaluation of G.723.1, one of the speech coders for IP telephone through continuous word recognition on Japanese speech corpus. Experimental results show that the recognition performance of G.723.1 coded speech is degraded compared to no coded speech. In this paper, we investigate these results.
497.	Shingo Kuroiwa, Satoru Tsuge, Hironori Tani, Masami Shishibori, Fuji Ren and Kenji Kita : Latent Semantic Indexing Based on Simple Principal Component Analysis, International Conference on Information-2002, Series of Information & Management Sciences, Vol.3, 172-177, Beijing, Jul. 2002. (Summary) In this paper, we propose to use the Simple Principal Component Analysis (SPCA) for dimensionality reduction of the vector space information retrieval model. The SPCA algorithm is a data-oriented fast method which does not require the computation of the variance-covariance matrix. In SPCA principal components are estimated iteratively so we also propose a criteria to determine the convergence. The optimum number of iterations for each principal component can be detemined using the criteria. Experimentally, we show that the SPCA-based method offers improvement over the conventional SVD-based method despite its small amount of computation.
498.	Satoru Tsuge, Shingo Kuroiwa, Masami Shishibori, Fuji Ren and Kenji Kita : An Evaluation of Japanese Speech Recognition Using ETSI Standard DSR Front-end, International Conference on Information-2002, Series of Information & Management Sciences, Vol.3, 372-376, Beijing, Jul. 2002. (Summary) This paper reports an evaluation of ETSI standard DSR (Distributed Speech Recognition) front-end through continuous word recognition on a Japanese speech corpus. Experimental results show that using non-quantized features in acoustic model training procedure can improve the recognition performance of DSR front-end features.
499.	Li Taihao, Fuji Ren and Kenji Kita : Extracting Japanese-Chinese Bilingual Word Paris with Maximum Entropy Model, Series of Information & Management Sciences, Vol.3, 33-37, Beijing, Jul. 2002. (Summary) In this paper,, we present an approach to construct a translation dictionary used in multilingual natural language processing such as machine translation. We use a learning and extracting method of bilingual word pairs from parallel corpora using the maximum entropy modeling. We are doing the experiment in Japanese and Chinese parallel corpora.
500.	Fuji Ren : Sensitive Word Concept and Its Application in Chinese Text Segmentation, ICCC2001,International Conference of Chinese Computing, Chinese Language e-Learning,, 333-340, Singapore, Nov. 2001. (Summary) The identification of words in Indo-European languages is a trivial task. However, this problem named text segmentation has been, and is still a bottleneck for various Asian languages, such as Chinese. There have been two main groups of approaches to Chinese segmentation: dictionary-based approaches and statistical approaches. However, both approaches have difficulty to deal with some Chinese text. To address the difficulties, we propose a hybrid approach using Sensitive Word Concept to Chinese text segmentation. Sensitive words are the compound words whose syntactic category is different from those of their components. According to the segmentation, a sensitive word may play different roles, leading to significantly different syntactic structures. In this paper, we explain the concept of sensitive words and their efficacy in text segmentation firstly, then describe the hybrid approach that combines the rule-based method and the probability-based method using the concept of sensitive words. Our experimental results showed that the presented approach is able to address the text segmentation problems effectively.
501.	Fuji Ren, Li Shigang and Kenji Kita : Automatic Abstracting Important Sentences of Web Articles, IEEE International Conference on System, Man, and Cybernetics, Vol.3, 1705-1710, Tucson, Oct. 2001. (Summary) Being increasingly popular, the Internet greatly changes our live. We can conveniently receive and send information via the Internet. With the information explosion in Web, it is becoming crucial to develop means to automatically extract important sentences from the Web articles. In this paper, we propose a method which uses both statistical and structural information in sentence extraction. In addition, following the analysis of human's extractions, several heuristic rules are added to filter out non-important sentences and to prevent similar sentences from being extracted. Our experimental results proved the effectiveness of these means. In particular, once the heuristic rules being added, a significant improvement has been observed. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICSMC.2001.973531 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-0035720436 (DOI: 10.1109/ICSMC.2001.973531, Elsevier: Scopus)
502.	Fuji Ren, Shi Hongchi and Shingo Kuroiwa : A New Machine Translation Approach using Multiple Translation Engines and Sentence Partitioning, IEEE International Conference on System, Man, and Cybernetics, Vol.3, 1699-1704, Tucson, Oct. 2001. (Summary) In this paper, we present a new machine translation (MT) approach using MT engines and sentence partitioning. A multiple engine MT system consists of several MT engines running in parallel, coordinated by a controller. Each engine is implemented using an existing MT technique and has its own characteristics. When translating a sentence, each engine translates it independently. If more than one engine translates the sentence successfully, the controller chooses the best translation according to a combining algorithm implemented using translation statistics. If no engine succeeds in translating the sentence, the controller partitions the sentence, coordinates the engines to translate its constituent simple sentences, and combines the partial translation results into a translation result for the whole input sentence. A complex sentence is partitioned based on conjunctives and punctuation marks such as comma and semicolon. We have developed a multiple engine MT system based on the above approach. The system consists of four independent MT engines. The experiments show that the proposed approach is effective for implementing practical MT systems. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICSMC.2001.973530 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-0035720474 (DOI: 10.1109/ICSMC.2001.973530, Elsevier: Scopus)
503.	Fuji Ren, Shi Hongchi and Zhon Qiang : A Hybrid Approach to Automatic Chinese Text Checking and Error Correction, IEEE International Conference on System, Man, and Cybernetics, 1693-1698, Tucson, Oct. 2001. (Summary) Automatic Chinese text checking and error correction is an important and difficult problem. Compared with automatic checking and error correction of Western text, automatic checking and error correction of Chinese text faces more challenges. The Chinese language has many characters and no delimiters separating words. It is impossible to detect and correct errors by penetrating into the inner composition of a character. In this paper, we describe some special features of Chinese characters and text and some statistical information obtained from a real world Chinese text corpus, and we present a hybrid approach that combines a rule-based method and a probability-based method to automatic checking and error correction of Chinese text. We also present an experimental system, HSACCCT (Hybrid System of Automatic Checking and Correction for Chinese Text), that implements this hybrid approach and some experimental results on real world Chinese text. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICSMC.2001.973529 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-0035723267 (DOI: 10.1109/ICSMC.2001.973529, Elsevier: Scopus)
504.	Shi Hongchi, Shang Yi and Fuji Ren : Using Natural Language to Access Databases on the Web, IEEE International Conference on System, Man, and Cybernetics, 429-434, Tucson, Oct. 2001. (Summary) As the traditional relational databases and the new XML document repositories are being widely used on the Web as information storage, there is a great need for easy access to the information sources, particularly through natural language interactions. In this paper, we present the design and implementation of an intelligent system that interacts with users using a natural language, English, and retrieves information from sources, for the users. The system consists of four major parts: part of speech tagging, query knowledge base, query formation, and answer synthesis. In implementation, the system first uses QTAG, a Hidden Markov Model based speech part tagger, to tag each word in the input sentence. Then, important words in the main phrase are identified. A thesaurus is applied to reduce the important words to basic keywords, which are used to query the database. The query is formed based on the query knowledge stored in the query knowledge base. Finally, the query result is synthesized into an English sentence, which is presented to the user as the answer. With an efficient part of speech tagger, intelligent subsystems for query formation and synthesis of query result, and user-friendly interface, the intelligent system can answer questions effectively. (Link to Publication Site) ● Publication site (DOI): 10.1109/ICSMC.2001.969850 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-0035725066 (DOI: 10.1109/ICSMC.2001.969850, Elsevier: Scopus)
505.	Fuji Ren : New Machine Translation Paradigm: Parallel Translation, CASEJ Symposium Series, Vol.2001, No.1, 17-28, Tokyo, Jul. 2001. (Summary) 機械翻訳では一番難し問題はいろいろな曖昧性の処理である．例えば，形態素解析における曖昧性，単語の曖昧性，品詞の曖昧性，文構造の曖昧性，意味構造の曖昧性などが挙げられる．本論文ではこのような核心の問題を解決するため，並列翻訳パラダイムを提案する．また，並列機械翻訳の原理，概念，そして実用手法を述べる．
506.	Fuji Ren and Shi Hongchi : Parallel Machine Translation: Principles and Practice, Seventh IEEE International Conference on Engineering of Complex Computer Systems, 249-259, Skovde, Jun. 2001. (Summary) Parallel Machine Translation (PMT) is a new machine translation paradigm that takes advantage of high-speed and large-memory computers and existing machine translation systems with different characteristics to solve the difficult machine translation problem. PMT is based on technologies of parallel computing, machine translation, and artificial intelligence. A PMT system consists of many machine translation procedures running in parallel, coordinated by a controller, to dissolve various ambiguities in machine translation. We have designed and implemented a PMT system based on the above approach at a coarse parallel level. The system consists of four independent machine translation subsystems. Each subsystem is implemented using an existing machine translation technique and has its own characteristics. In this paper, we present the principles and practice of PMT. We also present some results of experiments with our experimental PMT system and point out some future research on PMT. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-0034876465 (Elsevier: Scopus)
507.	Fuji Ren : A Hybrid Approach of Text Segmentation Based on Sensitive Word Concept for NLP, Second International Conference on Intelligent Text Processing and Computational Linguistics, 373-386, Mexico City, Feb. 2001. (Summary) Natural language processing, such as checking and correction of Texts, Machine Translation, and Information Retrieval, usually starts from words. The identification of words in Indo-European languages is a trivial task. However, this problem named text segmentation has been, and is still a bottleneck for various Asian languages, such as Chinese. There have been two main groups of approaches to Chinese segmentation: dictionary-based approaches and statistical approaches. However, both approaches have difficulty to deal with some Chinese text. To address the difficulties, we propose a hybrid approach using Sensitive Word Concept to Chinese text segmentation. Sensitive words are the compound words whose syntactic category is different from those of their components. According to the segmentation, a sensitive word may play different roles, leading to significantly different syntactic structures. In this paper, we explain the concept of sensitive words and their efficacy in text segmentation firstly, then describe the hybrid approach that combines the rule-based method and the probability-based method using the concept of sensitive words. Our experimental results showed that the presented approach is able to address the text segmentation problem effectively.
508.	Fuji Ren and Fan Lixin : Japanese-Chinese Machine Translation Using Very Large Corpora, The International conference on Information 2000, 160-167, Fukuoka, Oct. 2000. (Summary) 日英機械翻訳に比べると，日中機械翻訳研究が結構遅いが，幾つかの問題を解決しなければならない．特に機械翻訳規則を生成する際には大規模なコーパスが必要である．本論文では，日中機械翻訳システムを構築するため，大規模なコーパスの利用手法を提案する．まず，教科書などからコーパスを収集し，文単位でのアライメントを行う．そして，獲られた対訳文について解析し，翻訳規則を生成する．さらに，このような翻訳規則を利用してテストを行う．このようなテスト·修正·再テスト·再修正により，最終的な翻訳規則ベースを作成する．最後にこのような翻訳規則を開発した機械翻訳エンジンに組み込んで日中機械翻訳システムを構築する．実験により提案した手法の有効性を確かめることができた．
509.	Fuji Ren and Yoichi Takehara : Tool MKSF for Acquiring Super-Function in JAVA, IEEE International Conference on System, Man, and Cybernetics, Vol.4, 2473-2480, Nashville, Oct. 2000. (Summary) We have paid attention to the favors of Machine Translation (MT) users for a few years, and found that most users prefer that the system is fast, inexpensive, easy to control, and easy to update. This means that some times we do not need to aim a MT system with high fluency of the translations. At fact, usually we can not build such MT system which can get a high fluency of the translations. According the viewpoint, we have proposed a new MT paradigm called Super-Function Based Machine Translation (SFBMT) to try to address the MT user's requests. SFBMT uses Super-Function (SF) to translate without thorough syntactic and semantic analysis as most MT systems usually do. The SF is a function that shows the correspondence between original language sentence patterns and target language sentence patterns. One key point for building a SFBMT system is how to acquire the SF from the practical natural language phenomenon. In this paper, we present a method for aiding human to acquire the SF from parallel corpus, and describe the TOOL call MKSF. MKSF has been constructed in JAVA. A experimental MT system based on proposed method has been built using JAVA and some translation experiments have carried out. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-0034497347 (Elsevier: Scopus)
510.	Fuji Ren and Shi Hongchi : A General Ontology Based Multi-Lingual Multi-Function Multi-Media Intelligent System, IEEE International Conference on System, Man, and Cybernetics, 2362-2368, Nashville, Oct. 2000. (Summary) A large variety of information processing applications deal with natural language texts. Many such applications require extracting and processing the meanings of the natural language texts, in addition to processing their syntactic forms. In order to extract meanings from texts and manipulate them, a natural language processing system must have a significant amount of knowledge about the world and the domain of discourse. However, different kinds of knowledge are required for different languages, for different functions, and for different media. In this paper, we design a new general ontology based natural language processing system referred to as Multi-lingual Multi-function Multi-media Intelligent System (MMM-IS). MMM-IS is a complex system with multiple functions that can deal with multiple languages and multiple media. The general ontology consists of a static layer and a dynamic layer, and it provides a real world knowledge model for the natural language processing system. This paper presents the concept of MMM-IS and how to build MMM-IS for real applications. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-0034504579 (Elsevier: Scopus)
511.	Fuji Ren : Dialogue Machine Translation Using Multiple Translation Processors, The 11th International Workshop on Database and Expert Systems Applications, 143-148, London, Sep. 2000. (Summary) 会話文機械翻訳において一番難しいタスクがいかに会話文における非文法的な表現を処理するかである．従来の多くの機械翻訳システムはこのような非文法的な表現に対処できない．本論文では，このような問題を解決するために，複数翻訳エンジンを用いる新しい方法を提案する．複数の翻訳エンジンがあるが，各エンジンが各自の特徴を持って対応できる会話文表現も異なる．もし一つのエンジンが成功すると，このエンジンにより獲られた翻訳を最終結果として出力する．複数のエンジンが翻訳成功すると，予め決めた重みにより最尤な結果を最終翻訳とする．
512.	Fuji Ren : A Parallel Approach to Incorporating Face Image Information into Dialogue Processing, The International Conference on Parallel and Distributed Methods for Image Processing IV, Vol.4118, 67-78, San Diego, Jul. 2000. (Summary) 会話文には非文法的な表現が多いが，このような表現の処理が極めて難しい．また，同じ表現でも色々な異なる意味を表現する．即ち，話者の感情状態により会話の意味が違う．本論文では，話者の顔表情イメージ情報を活かし新しい会話処理アプローチを提案する．まず，会話文を幾つかの処理器を用い同時に処理するが，曖昧性が有るときには，イメージ情報を用い解決する．
513.	Fuji Ren and Nie Jianyun : Automatic Extraction of Important Sentences using Statistical Information and Structural Features, International Conference on Artificial Intelligence and Soft Computing 2000, 479-486, Banff, Jul. 2000. (Summary) 情報の氾濫によって長い文章から重要なセンテンスを自動的に抽出する方法の開発が不可欠になってきている．この論文では統計的·構造的情報を用いてセンテンスの抽出を行う手法を述べる．さらに手動での抽出を分析し，いくつかの発見的な規則を付与して，重要でないセンテンスをフィルタリングし，よく似たセンテンスが抽出されることがないようにした．我々の実験結果はこれらの手法の有効性を証明している．特に一度発見的規則が付与された場合に大きな改善が観測された．
514.	Fuji Ren : Multi-Engine Based Machine Translation and WMV Algorithm, The Fifth International Conference on Computer Science and Informatics, 402-406, Atlantic City, Apr. 2000. (Summary) 会話の機械翻訳が抱える難問の一つは，自然な会話で使われる，非文法的，不完全または不適格な不規則表現を翻訳することである．しかしながら，既存の機械翻訳システムは大抵不規則表現を含む発話を受け入れない．翻訳の質を高め，機械翻訳システムをユーザのニーズに合わせやすくするために，我々は新しいマルチエンジンに基づく機械翻訳のアプローチを提案する．このアプローチでは，次のようないくつかの異なる翻訳エンジンを使って原言語分析と目的言語生成を同時に行う．(I)役割に基づく翻訳エンジン(II)例に基づく翻訳エンジン(III)家族モードに基づく翻訳エンジン(IV)スーパー関数に基づく翻訳エンジンである．ひとつ以上の翻訳エンジンが有効な時は最良の結果を選択するのが難しく，既存のマルチエンジンの手法では結果が様々であった．マルチ選択の問題を解決するため，我々はWMV(評価最大値)アルゴリズムを提案する．各エンジンの評価を実験と統計的情報によって決定し，提案手法に基づくプロトタイプシステムを構築し，いくつかの実験を行った．実験結果は我々の手法が頑強な対話翻訳の導入と実用的な会話機械翻訳システムの開発に効果的であることがわかった．
515.	Shi Hongchi, Li Hongzheng and Fuji Ren : Encoding/Decoding video streams on the VGI parallel computer, Proceedings of the IASTED Parallel and Distributed Computing and Systems, 1-6, Boston, Nov. 1999. (Summary) VGIパラレル·コンピュータとはビデオ，グラフィック，画像処理アプリケーションのストリームデータを処理するためのマルチスレッド化された静的データフロー·コンピュータのことである．パラレルVGIコンピュータは，再構成可能なコミュニケーション·ネットワ-クにつながった多数のプロセッサーで構成されている．2つのつながったプロセッサーは，コニュニケーションや同期にシンプルなハンドシェイク認証のプロトコルを使う．VGIパラレル·コンピュータはストリームデータ処理に効率的な構造を持ち，ストリームデータの処理アルゴリズムをこの様な構造へと発展させることは未だ困難である．この論文ではVGIコンピュータ上でビデオストリームをエンコード/デコード化するためのアルゴリズムを提案する．
516.	Zhou Qiang and Fuji Ren : Automatic Inference for Chinese Probabilistic Context-Free Grammar, the 5th Natural Language Processing Pacific Rim Symposium, 73-78, Beijing, Nov. 1999. (Summary) この論文は中国語の確率的文脈自由文法への新しいインターフェースのアプローチを提唱する．これはブラケットマッチングの理論体系に基づいている．このアルゴリズムによって，構成境界情報と，自動構築規則とtreebank統計を混合した初期ルールを付与した練習テキストを利用して，言語学的に動機付けされた広範囲の中国語PCFG規則が生成される．現在の実験結果はこのアルゴリズムの効率的な習得と生成された規則の高い信頼性を示している．
517.	Fuji Ren, Fan Lixin and Nie Jianyun : SAAK Approach: How to Acquire Knowledge in an Actual Application System?, Proceedings of the IASTED International Conference on Artificial Intelligence and Soft Computing, 136-140, Honolulu, Aug. 1999. (Summary) 翻訳規則の獲得は規則に基づく機械翻訳における重要な問題である．完全に自動的な獲得には大量の注釈付きの例文が必要である．この論文では必要に応じて追加的な情報を与えるユーザとインタラクションする，半自動的獲得アプローチについて翻訳例を用いて述べる．
518.	Fuji Ren : SFBMT Project and Tool Development for Acquisition of Super-Functions, Proceedings of the IASTED International Conference on Artificial Intelligence and Soft Computing, 462-467, Honolulu, Aug. 1999. (Summary) 我々はスーパー関数に基づく機械翻訳(SFBMT)と呼ばれる新しいパラダイムを提案している．このパラダイムは高性能，低価格，ユーザ·フレンドリー，学習効果などの機械翻訳のユーザの要望に応えるものである．この論文では原言語から目的言語への翻訳文の作成に，どのようにSFBMTを利用するかについて，またパラレルコーパスから手動でのスーパー関数獲得を補助するMKSFと呼ばれるツールについて述べている．
519.	Fuji Ren and Zaima Yasumichi : Automatic Derivation of Programs for Image Processing from Natural Language Descriptions, Proceedings of International Conference of Parallel and Distributed Methods for Image Processing, 62-73, Denver, Jul. 1999. (Summary) この論文ではAIDPG(インタラクティブ·プロトタイプシステム)について述べる．これは自然言語の記述からコンピュータプログラムを導くシステムであり，どのように自然言語を分析し，知識を用いて曖昧性を解決し，プログラムを生成するかを表すものである．AIDPGは自然言語入力モデル(NLI-Model)，自然言語分析モデル(NLA-Model)，プログラム生成モデル(PGG-Model)，ヒトと機械のインターフェース管理モデル(HMC-Model)によって構成されている．PGGモデルには3つのサブモデルがあり，これはプログラム構造管理サブモデル，データ構造·タイプ管理サブモデル，プログラムベース管理サブモデルである．我々は日本語で記述された算数の問題を用い，AIDPGに通してCプログラムを走らせることを可能にした．現段階のAIDPGは基本的なものであるが，有意義な結果を得ることが出来た．
520.	Fuji Ren : MMM and New Machine Translation Approach, Proceedings of International Conference on Machine Translation & Computer Language Information Processing, 38-44, Beijing, Jun. 1999. (Summary) この論文ではMMM(多言語·多機能·多メディア)と呼ばれる新しい概念について述べる．MMM-IS(知能システム)は一般的なオントロジーに基づいて構築されている，大きなシステムである．MMM-ISによって，機械翻訳システム等の自然言語処理システムに残された多くの問題を解決できる．しかしながらMMM-ISの構築には時間がかかり現在時点では実用できない．SFBMT(スーパー関数に基づく機械翻訳)と呼ばれる新しい機械翻訳へのアプローチの実用化について提案する．この論文では原言語から目的言語への翻訳文の作成に，どのようにSFBMTを利用するかについて，またパラレルコーパスから手動でのスーパー関数獲得を補助するMKSFと呼ばれるツールについて述べている．
521.	Fuji Ren and Fan Lixin : Dialogue Machine Translation Using Multi-Processors, Proceedings of International Conference on Machine Translation & Computer Language Information Processing, 100-105, Beijing, Jun. 1999. (Summary) 自然な会話では，話し手は言い間違えたり，不規則な表現を使うことがある．会話の機械翻訳が抱える難問の一つは，自然な会話で使われる，非文法的，不完全または不適格な不規則表現を翻訳することである．しかしながら，既存の機械翻訳システムは大抵不規則表現を含む発話を受け入れない．この論文ではCooperative Distributed自然言語処理モデル(CDM)に基づく，マルチプロセッサを使った会話機械翻訳(DMTMP)を提案している．DMTMPでは次のようないくつかの異なるタイプの手法を使って原言語分析と目的言語生成を同時に行う．(1)全情報処理(又は統語論的·意味論的制約に基づく処理)(2)統語論的省略処理(又は意味論的制約に基づく処理)(3)意味論的省略処理(又は統語論的制約に基づく処理)(4)例に基づく処理(5)家族モードセンテンス分割に基づく処理(6)スーパー関数に基づく処理．提案した手法に基づくDMTMPシステムのプロトタイプは我々の開発したSWKJCシステム内に構築した．実験を行った結果，この論文で提案された手法はrobustな(くだけた?)対話翻訳の導入と実用的な会話機械翻訳システムの開発に効果的であることがわかった．
522.	Fuji Ren : A Hybrid Approach to Automatic Checking and Correction of Chinese Texts, Proceedings of Seventeenth IASTED International Conference on Applied Informatics, 17-22, Innsbruck, Feb. 1999. (Summary) 英語テキストと比べると，中国語テキストを自動的にチェック·修正することはより難しい．英語が単語の綴りを検証して間違いを検出·修正するのに対し，漢字の内的構造に入り込んで検証することは不可能である．中国語の文字やテキストの特徴，実際的な中国語テキストコーパスから得た統計的情報は，中国語テキストの自動的なチェックや修正を困難にしている．この解決策として我々は規則に基づく手法と可能性に基づく手法の混合的なアプローチを提案する．このアプローチに基づくHSACCCT(中国語テキスト自動チェック·修正ハイブリッドシステム)と呼ばれるプロトタイプシステムを構築し，百五十万語の実際的なテキストを用いて実験を行った．中国語テキストに共通する間違いのタイプについてまず分析し，次にHSACCCTで利用したアルゴリズムと実験結果について詳細を述べる．
523.	Davis Mark and Fuji Ren : Automatic Japanese-Chinese Parallel Text Alignment, Proceedings of 1998 International Conference on Chinese Information Processing, 452-457, Beijing, Nov. 1998. (Summary) パラレルテキストは翻訳者に訳例を見せるのみならず，用例文に基づく翻訳技術において両言語の対応語句の抽出に有用である．パラレルテキストの調整(alignment)は，異なる言語文書間の対応する句をマッチングさせることを含む．我々はChurchとGaleによって提唱されたテキスト調整に対する様々な統計的アプローチを開発し，日本語と中国語のパラレルテキストに用いた．この手法はセンテンスの文字の長さに基づいており，言語間の引用における違いを扱うべくいくつかの修正を加えたものである．我々の手法によって970の調整のうち883.7%にあたる12の正しい調整が得られ，有効性が証明されたが，中英，英仏の言語間で用いられている関連アプローチほど正確ではない．
524.	Fuji Ren, Nie Jian-Yun, Fan Lixin and Jian Youliang : Semi-Automatic Acquisition of Translation Knowledge from Examples, Proceedings of 1998 International Conference on Chinese Information Processing, 444-451, Beijing, Nov. 1998. (Summary) 規則に基づいた機械翻訳において重要な問題は翻訳知識の獲得である．これまで獲得の自動化に関する数多くの研究が行われてきたが，いずれも注釈付きの膨大な例文を必要とする．この論文では，日本語と中国語の翻訳例文から翻訳知識を半自動的に獲得する手法について述べる．これは知識獲得のプロセスにおいて必要に応じて，ユーザ(言語学者)が翻訳例文の規則化に必要な追加情報や制約を与えるものである．半自動的なアプローチは全自動による知識獲得より例文が少なくてすむという点でより効率的である．獲得した知識を機械翻訳システムと統合し，翻訳の質の向上についても述べる．
525.	Fuji Ren and Luo Zhensheng : A Hybrid Approach to the Real World Text Segmentation, Proceedings of 4th International Conference on Computer Science and Informatics, Vol.3, 243-249, North Carolina, Oct. 1998. (Summary) テキスト·セグメンテーションにとって，言葉の特徴や統計的情報などの独自の性質は非常に扱いにくい問題である．テキスト·セグメンテーションによって主に3つの問題が解決される:(1)辞書の体系と構造およびセグメンテーション·アルゴリズム(2)曖昧性を解決するアルゴリズム(3)人名，地名，機関名等の新しい言葉の発見．我々は中国語のテキストのセグメンテーションに対して，規則に基づく手法と可能性に基づく手法の混合的なアプローチを提案する．この論文では我々はまず，選択された語の初期辞書に基づいた，高性能の単一スキャニング·セグメンテーション·アルゴリズムを提唱する．次にセグメンテーションにおける曖昧性の検出と解決について議論し，新しい単語を発見するアルゴリズムについて述べる．最後に2千万語から成る中国語コーパスに基づいて行った実験の結果について報告する．
526.	Fuji Ren, Fan Lixin and Nie Jianyun : Chinese Sensitive Words and Their Impact in Machine Translation, The 27th annual meeting of the Linguistic Association of the South-west, 1-8, Arizona, Oct. 1998. (Summary) A crucial problem in rule-based machine translation is the acquisition of translation knowledge. Many studies have been conducted for automatic acquisition in the past, but they require a great deal of annotated examples. In this paper, we describe a semi-automatic acquisition from translation examples in Japanese-Chinese environment. Whenever necessary, the process interacts with a user who will provides additional information and constraints for generalizing the translation examples. The semi-automatic approach is more efficient in the sense that less examples are required than automatic approaches. Once the acquired knowledge is integrated with an MT system, we observe an improvement in translation quality.
527.	Fuji Ren : Outline of SFBMT Project, Language Engineering, Proceedings of The 4th Joint Conference on Computational Linguistics, 305-312, Beijing, Aug. 1997. (Summary) 本論文ではGBMTの質と翻訳速度を改善するため，新しい機械翻訳手法を提案した．提案した手法では従来の構文解析や意味解析を行わず，文の構造的なパターンに対応することにより翻訳を行う．小規模な実験を行い，提案した手法の実現可能性を確かめた．
528.	Fuji Ren : A Japanese-Chinese Machine Translation System Based on Translation Rules Acquired from Corpora, The 25th annual meeting of the Linguistic Association of the South-west, 1-8, Baton Rouge,, Oct. 1996. (Summary) 本論文ではルールに基づく日中機械翻訳システムを述べる．我々の構築したシステムにおいてはそのルールはコーパスから獲得された．従来のコーパス方法と異なり，本論文ではコーパスから抽出したルールとコーパスと分離して，コーパスを機械翻訳エンジンに組み込んでいるが，コーパスはシステムに組み込まない．そして，本論文では幾つかの実験を行い，いろいろな考察を行った．
529.	Fuji Ren : Cooperative Distributed Processing for Machine Translation, Proceedings of International Conference on Chinese Computing 96, 226-234, Jun. 1996. (Summary) 本論文では分散·協調機械翻訳アプローチを提案した．分散とは機械翻訳における問題を幾つかに分解し幾つかのサブ問題になる．協調とは複数のエンジンから得られた解答を総合的に判断しその最適な解を求める．本論文では現在のコンピュータのパワーと自然言語処理技術を融合し実用化できる機械翻訳方式を提案した．この方式では，全情報モジュール，構文情報モジュール，意味情報モジュールがある．このような複数のモジュールは各々のサブ問題に適用し，局部解を求める．我々は複数プロセスの結果から最尤結果を選択するアルゴリズムを開発した．本論文では，分散·協調メカニズム，実験結果の検討について述べる．
530.	Fuji Ren : Techniques for Machine Translation System Using Empirical Knowledge, Proceedings of Advances and Applications on Computational Linguistics, 269-301, Shanghai, Oct. 1995. (Summary) 人間のコミュニケーシュンでは経験知識がときどき利用されている．このような経験知識を機械翻訳システムに導入できれば質の高い機械翻訳を構築することができると考える．実言語現象から獲得した経験的知識を活用してその経験知識を機械翻訳システムに導入した．これにより，入力の多様性に対応できる頑健的システムの実現が期待されている．本論文ではまず経験知識の表示方法，そして経験知識の利用手法を提案した．そして，対話文の翻訳を例として実験と考察を行った．
531.	Fuji Ren : Experiments of Resolving Structural Ambiguities in Machine Translation, The 24th annual meeting of the Linguistic Association of the South-west, 7-14, Las Cruces, USA, Oct. 1995. (Summary) 機械翻訳システムを構築する際には一番困難な問題の一つとしては曖昧性を如何に解消するかということである．その中に構造的な曖昧性が難しくて，あまり解決策が提案されていない．本論文では幾つかの構造的な曖昧関係を検討し，その中の一つ重要な特性を明らかにした．これは可保留曖昧関係である．本論文ではこの可保留曖昧関係の機械翻訳方法を提案した．
532.	Fuji Ren and Fan Lixin : Persisting Structural Ambiguities and Its Application in Japanese-Chinese Machine Translation, Proceedings of Informational Conference of Recent Advances in Natural Language Processing, 301-307, Tzigov Chark, Bulgaria, Sep. 1995. (Summary) 本論文では，日中機械翻訳における可保留曖昧関係という概念を提案した．可保留曖昧関係は原言語でその曖昧性を解決されずに，中国語に翻訳することができる日本語の構造的な曖昧な表現である．通常，ある言語を，異なる言語族の他方に翻訳する場合，構造の曖昧な表現を解消しなければならない．しかしながら，日本語と中国語はほとんど文構造上に同じ言語族に属していないが， RSAを可能にして，それらの文のいくつかの部分は類似している．本論文ではこの方法に基づいた実験のシステムを構築し，翻訳実験を行った．
533.	Fuji Ren : On New Generation Machine Translation Using Empirical Knowledge, Proceedings of The Second Academic Conference of Young Scientists, 134-140, Beijing, May 1995. (Summary) 経験的な知識を用い，次世代機械翻訳システムを構築する新しい技術を研究した．特に経験的な知識の定義，経験的な知識の獲得，経験的な知識の機械翻訳への応用手法を提案した．一部アルゴリズムについて，実験によりその有効性を確認した．
534.	Lixin Fan, Fuji Ren, Yoshikazu Miyanaga and Koji Tochinai : Chinese-Japanese Machine Translation System Using Sentence Partition Method, Proceedings of International Conference on Chinese Computing, 1-7, Singapore, Jun. 1994. (Summary) 一般に中国人では，日本語の学習に際してまず日本語のいくつかの格助詞を学び，その後は常用文型を中心に学習する．我々はこのような人間の言語学習の方法が機械翻訳に効果的であると考え，文の分解による機械翻訳手法を提案した．本論文ではこの手法を中日機械翻訳システムへの応用について述べる．まず，中国語文を基本文と関連語に分解する．すなわち，長い文を短く文に分解する．そして，分解された短い文を解析し翻訳する．最後に，各部分の訳文と知識ベースを用い全文の訳文を合成する．このようなメカニズムに基づく中日機械翻訳実験システムを構築し，翻訳実験を行った．本論文では提案した手法の理論的な分析および実験結果の考察について述べる．

Proceeding of Domestic Conference:

1.	Ikegami Tatsuya, Fuji Ren, Shun Nishide and XIN KANG : Tweet日本語感情コーパスに対するBERTの効果の検証, 情報処理学会全国大会講演論文集, 527-528, Mar. 2021.
2.	Shogo Terao, Shun Nishide, XIN KANG and Fuji Ren : ロボット教師における特定人物の音声の自動生成, 情報処理学会第83回全国大会講演論文集, 225-226, Mar. 2021.
3.	Naoyuki Kadota, Shun Nishide, XIN KANG and Fuji Ren : ロボット教師における特定分野のQAシステムの構築, 情報処理学会第83回全国大会講演論文集, 563-564, Mar. 2021.
4.	Koji Masago, Shun Nishide, XIN KANG and Fuji Ren : 神経力学モデルを用いた楽譜の学習とコード系列からの和音生成, 第83回情報処理学会全国大会, Vol.2021, No.2, 451-452, Mar. 2021.
5.	Yusuke Kubono, Shun Nishide, XIN KANG and Fuji Ren : 神経力学モデルによる複雑図形の学習と生成, 情報処理学会第83回全国大会, Vol.2021, No.2, 449-450, Mar. 2021.
6.	Naoto Yamasaki, XIN KANG, Shun Nishide and Fuji Ren : ロボット教師による特定分野の記述式問題の判定について, 電子情報通信学会総合大会講演論文集, Mar. 2020.
7.	Jumpei Fusanobori, XIN KANG, Shun Nishide and Fuji Ren : 単語の感情属性を活かしたロボット教師の表情生成, 電子情報通信学会総合大会講演論文集, Mar. 2020.
8.	Shogo Terao, XIN KANG, Shun Nishide and Fuji Ren : ロボット教師における特定人物の音声の自動生成, 電子情報通信学会総合大会講演論文集, Mar. 2020.
9.	Naoyuki Kadota, XIN KANG, Shun Nishide and Fuji Ren : ロボット教師における特定分野のQAシステムの構築, 電子情報通信学会総合大会講演論文集, Mar. 2020.
10.	Mako Kawano, Shun Nishide, XIN KANG and Fuji Ren : 深層モデルを用いた画像系列の特徴量自己組織化と映像生成, 情報処理学会全国大会講演論文集, 2-289-2-290, Mar. 2020.
11.	Fusei Nomoto, Shun Nishide, XIN KANG and Fuji Ren : 構造に注目した神経力学モデルを用いた漢字の筆跡ダイナミクスの学習, 情報処理学会全国大会講演論文集, 2-281-2-282, Mar. 2020.
12.	Yusuke Kubono, Shun Nishide, XIN KANG and Fuji Ren : ペンの持ち上げを考慮した神経力学モデルによる描画図形予測と生成, 情報処理学会全国大会講演論文集, 2-283-2-284, Mar. 2020.
13.	Koji Masago, Shun Nishide, XIN KANG and Fuji Ren : リカレントニューラルネットワークを用いた未学習のコードからの楽譜生成, 情報処理学会全国大会講演論文集, 2-279-2-280, Mar. 2020.
14.	Ryosuke Yasumura, Shun Nishide, XIN KANG and Fuji Ren : アームロボットを用いた発達的描画モデルの構築, 日本ロボット学会学術講演会, Sep. 2019.
15.	Kensuke Kondoh, Shun Nishide, XIN KANG and Fuji Ren : Kinectを用いた神経力学モデルによる人の身体動作のクラスタリング, 情報処理学会全国大会講演論文集, 2-519-2-520, Mar. 2019.
16.	Shota Inui, Shun Nishide, XIN KANG and Fuji Ren : 深層学習を用いた人の行動認識と感情生成, 情報処理学会全国大会講演論文集, 2-517-2-518, Mar. 2019.
17.	Ryosuke Yasumura, Shun Nishide, XIN KANG and Fuji Ren : アームロボットのための発達的な描画学習モデルの基盤システム構築, 情報処理学会全国大会講演論文集, 2-313-2-314, Mar. 2019.
18.	Mizuho Amoh, Shun Nishide, XIN KANG and Fuji Ren : 音符・コード系列に注目した神経力学モデルによる音楽情報の階層的学習, 情報処理学会全国大会講演論文集, 2-375-2-376, Mar. 2019.
19.	Misaki Mori, Shun Nishide, XIN KANG and Fuji Ren : 神経力学モデルを用いた部分描画系列からの描画図形予測, 情報処理学会全国大会講演論文集, 2-285-2-286, Mar. 2019.
20.	Yuzuki Nonaka, Shun Nishide, XIN KANG and Fuji Ren : ペンの持ち上げを考慮した神経力学モデルによる手書き漢字の学習, 情報処理学会全国大会講演論文集, 2-255-2-256, Mar. 2019.
21.	Hiroki Urakami, Shun Nishide, XIN KANG and Fuji Ren : Human Robot Interaction System Based on Emotion State Transition in Continuous Emotion Space, 情報処理学会全国大会講演論文集, 2-399-2-400, Mar. 2018.
22.	Tadayoshi Yasuda, Shun Nishide, XIN KANG and Fuji Ren : Hierarchical Learning of Primitives Using Neural Network Model, 情報処理学会全国大会講演論文集, 2-219-2-220, Mar. 2018.
23.	Yuki Sugimoto, Fuji Ren, Shun Nishide and XIN KANG : 心的状態遷移ネットワークに基づく感情会話システムの構築, 言語処理学会年次大会, 658-661, Mar. 2018.
24.	Kazuyuki Matsumoto, Fuji Ren, Minoru Yoshida and Kenji Kita : 絵文字を手がかりとした俗語感情コーパスの拡張, 言語処理学会第24回年次大会発表論文集, 797-800, Mar. 2018. (Summary) 絵文字が含まれていない文からでも，絵文字を推定することができれば，感情推定が可能になると考える．本論文では，俗語と絵文字を両方含む多量のコーパスを文字レベルで学習させ，絵文字推定器を作成し，俗語を含んだ発話文コーパスへの感情タグ付け手法を提案する． (Keyword) emoji / slang / emotion / corpus
25.	Yuko Takata, Shun Nishide, XIN KANG and Fuji Ren : Learning Drawing Sequences Using Recurrent Neural Network Model, 情報処理学会全国大会講演論文集, 2-489-2-490, Mar. 2018.
26.	Setsu Yoshie, XIN KANG, Shun Nishide and Fuji Ren : Extraction emotion from spoken language based on the language information, The 31st Annual Conference of the Japanese Society for Artificial Intelligence, Vol.0, No.0, 1-2, May 2017.
27.	Yoshie Setsu, XIN KANG, Shun Nishide and Fuji Ren : Extraction emotion from spoken language based on the language information, The 31st Annual Conference of the Japanese Society for Artificial Intelligence, 1-2, May 2017.
28.	Jiawen Deng and Fuji Ren : Sentiment analysis of Chinese corpus based on emotional lexicon, 2017年電子情報通信学会総合大会, D-5-2-29, Mar. 2017. (Keyword) 対話破綻検出 / 感情推定 / 分散表現
29.	Kazuyuki Matsumoto, Fuji Ren, Minoru Yoshida and Kenji Kita : 感情表出傾向の分析による対話破綻検出, 言語処理学会第23回年次大会発表論文集, 158-161, Mar. 2017. (Summary) 本研究では，ユーザの感情の変化に合わせてシステム自身の感情を表出させることができないために起こる対話破綻について，発話文から推測可能な感情傾向の比較により検出する手法を提案する．具体的には，発話文の分散表現ベクトルをもとに感情が表出されている強度を推定するモデルを用い，直前の 2 発話における推定結果との類似度の計算を行うことで，そのパターンを特徴量として対話破綻のラベルを推定する．評価実験では，提案手法を用いた対話破綻ラベルの推定をおこない，文の分散表現ベクトルの類似度パターンによる手法との比較をおこなう． (Keyword) 対話破綻検出 / 感情推定 / 分散表現
30.	Kazuyuki Matsumoto and Fuji Ren : 慣用句感情コーパスの構築および慣用句感情表現辞書の拡張, 言語処理学会第22回年次大会講演論文集, Mar. 2016.
31.	Shibasaki Hidenori, Shun Nishide and Fuji Ren : 人と自然なコミュニケーションのためのActroidの人間らしい動作デザイン, 第33回日本ロボット学会学術講演会講演論文集, Sep. 2015.
32.	Ohnishi Tsubasa, Kazuyuki Matsumoto, Kenji Kita and Fuji Ren : Relation Analysis on Emotion and EEG Fluctuation in Dialogue, 平成24年度電気関係学会四国支部連合大会講演論文集, 95, Sep. 2012. (Summary) 脳波等の患者から発信される情報が重要なのはいうまでもないが，患者からの情報のみに頼るのではなく，介護を行う側の意識を変化させることが，より重要だと考える．本研究の最終目的は言葉が被介護者の感情にどのように影響するかを言語情報から予測することである．このような予測が可能になれば，患者の心を傷つけるような言葉を未然に防ぐことができる．本研究では，共感を分析しやすい対象として，演劇シナリオを用いることにした．演劇シナリオは，一般的な対話と比較すると，演出を重視しているためか，感情的な表現が多用されている特徴がある．介護場面などでは，演劇口調で話すことはほとんどないと考えられるが，本研究ではこうした感情表現の多用により，脳波に明確な変化が起きることを期待する． (Keyword) 対話分析 / 脳波変化
33.	Kazuyuki Matsumoto, Onishi Tsubasa, Kenji Kita and Fuji Ren : Construction and Analysis of Scenario Dialogue Emotion Corpus, 第11回情報科学技術フォーラム(FIT2012)講演論文集, Vol.2, 242-243, Sep. 2012. (Summary) 従来，言語・音声・画像といった情報からの感情推定を目的とした研究が多くの研究者によって行われてきたが，感情を表面的な情報から得るには限界がある．この理由として，感情は内在的な反応であるため，表情や行動を伴わないことも多いことがあげられる．しかし，発話者同士が親密な関係であればある程，感情の変化に伴う相手の言葉遣いの微細な変化に気付くことがある．このような言葉遣いの細やかな変化を検出できれば，対話における感情推定精度を向上できる可能性がある．徳久らは，発話文の文末表現に着目したが，言葉遣いの細やかな変化は，文末表現のみに表れるものではないと考えられる．たとえば，相手が普段使用しないような単語や慣用句を使用する場合でも，何かしら相手の心境の変化を察することもある．本研究では，話者の発話時における感情と，発話役割や文体との関係を調べる準備段階として，対話を記述したコーパスに感情，発話役割，文体タグの付与を行なった．このコーパスを分析することで，相手発話のどのような要素が影響して感情が変化するかを考察する． (Keyword) シナリオコーパス / 対話処理 / 感情推定
34.	Kazuyuki Matsumoto, 吉岡伸浩, Kenji Kita and Fuji Ren : うつキーフレーズと感情変動に基づくブログからのうつ検出手法, 言語処理学会第18回年次大会講演論文集, 1126-1129, Mar. 2012. (Summary) 我々は，ブログの書き手に，うつ傾向があることを自覚させることにより，うつ病の早期発見・早期治療に役立てることができると考えた．まず，うつ傾向の有無を，ブログ内容から推定することができるか否かをテキスト分類手法を用いた実験により明らかにし，どのような特徴がうつ判定に有効であるかを調査する．また，人間の心の変化をとらえるための特徴として，時間経過に伴う記述内容の変化から読み取れる感情状態の変化がある．多くのブログが，毎日の出来事や心情を時系列順に書き記したものであるため，そこから時間的変化を得ることが出来る．本稿では，うつ特有の言葉遣いを収集したうつキーフレーズ辞書に基づくうつ検出手法と，感情状態の変化に基づいたうつ検出手法を提案する． (Keyword) natural language processing / うつ検出 / ブログ
35.	吉岡直輝, Kazuyuki Matsumoto, Kenji Kita and Fuji Ren : 印象尺度に基づいた文章言い換え手法, 言語処理学会第18回年次大会講演論文集, 425-426, Mar. 2012. (Summary) 本稿では文中の単語を，同じ意味の，別の印象を持つ単語に置き換えることで，印象の違った文に変換する手法を提案する．友人や家族とコミュニケーションをとる際に用いるような単語の印象を，Casual(柔かい表現)，目上の人とコミュニケーションをとる際に用いるような単語の印象をFormal(堅い表現)の尺度と定義し，新聞記事とブログを基に，単語のCasual/Formalの印象付与を自動で行う．新聞記事は短い文で的確にニュースのポイントを読者に伝えるため，会話では使用されることが少ない漢字を多く用いる．このことから，新聞記事で多く用いられる単語をFormalな単語として分類する．ブログは個人的な体験や日記を掲載し，臨場感を出すためにくだけた会話表現を多く用いる傾向がある．このことから，本実験では，ブログで多く用いられる単語はCasualな単語として分類する． (Keyword) natural language processing / 言い換え / 印象
36.	平尾卓也, Kazuyuki Matsumoto, Kenji Kita and Fuji Ren : コーパスに基づく雑談を目的とした発話役割同定, 言語処理学会第18回年次大会講演論文集, 109-110, Mar. 2012. (Summary) 我々は，コーパスに基づく雑談を目的とした発話役割の同定の研究を行っている．西原らは発話役割の一部は助詞・助動詞の組み合わせで表されるとし，助詞・助動詞の意味を用いたルールによって発話役割の同定を行った．そこで本稿では品詞情報を用いた雑談の発話役割に有効な重みを模索し，コーパスに基づく雑談を目的とした発話役割の同定手法を提案する． (Keyword) natural language processing / 発話役割 / 雑談 / corpus / 形態素2-gram
37.	Li Yang, Kazuyuki Matsumoto, Kenji Kita and Fuji Ren : Automatic Construction of Japanese-Chinese Word Dictionary on Super-Function Extraction for Japanese-Chinese Machine Translation, 第10回情報科学技術フォーラム講演論文集, Vol.2, 221-222, Sep. 2011. (Summary) 本研究ではスーパー関数を用いた日英機械翻訳の利点と問題点を考察し，スーパー関数に基づく機械翻訳を用いて日中機械翻訳システムの試作を行う．また，新たに提案したSFの変数の拡張についても述べる．提案手法では変数となる品詞の種類が多くなるため，訳語を適切に選択するために，参照する単語辞書の自動作成手法を提案する．最後に，提案手法による自動翻訳実験を行い，スーパー関数に基づく日中機械翻訳の精度を向上するには，対象とする例文に応じた対訳単語辞書が必要であることを明らかにする． (Keyword) machine translation / スーパー関数 / 日中機械翻訳 / 訳語選択 / 辞書構築
38.	Kazuyuki Matsumoto, Kenji Kita and Fuji Ren : Estimating Emotion of Wakamono Kotoba Based on Similarity of Example Sentences, 第10回情報科学技術フォーラム講演論文集, Vol.2, 281-284, Sep. 2011. (Summary) 若者言葉は，既存の語の言い換えたものであったり，省略表現も多いが，複合的な意味を持つ語や，既存の概念には属さない語も多い．こうした語のために，新語義を定義する必要があるが，その定義方法について未解決の問題が多い．我々の研究の目標は，若者言葉を含む文からの感情推定である．若者言葉を特徴として感情推定を行う際に，若者言葉を，その意味や用法，さらには感情などで分類することができれば感情推定の精度向上につながると考えられる．そこで，本稿では，若者言葉の用例に基づき，感情表現に関する情報を抽出することで，若者言葉の感情を推定する手法を提案する． (Keyword) 感情認識 / sentience computer / 若者言葉
39.	Masaki Mifune, Motoyuki Suzuki, Fuji Ren and Kenji Kita : クラスタリングに基づくGMM学習法による話者のモデル構築, IEICE Technical Report, Vol.SP2011, Jul. 2011.
40.	Yuki Hashimoto, Motoyuki Suzuki and Fuji Ren : 訳語候補を手がかりとするFrameNetを用いた日本語文への意味役割付与, 言語処理学会第17回年次大会予稿集, Mar. 2011.
41.	Kazuyuki Matsumoto and Fuji Ren : 感情推定における若者言葉の影響, 言語処理学会第17 回年次大会発表論文集, 846-849, Mar. 2011. (Summary) 若者言葉は，既知語に置き換えることが不可能な新しい概念の語や，既知語と同じ表記であるが若者言葉としてはまったく別の意味になる語も存在する．こういった語が感情を表現する場合，既知語に変換する方法を用いても効果が期待できない．そこで本研究では，若者言葉による感情表現の特徴を用例から調査する必要があると考え，若者言葉を含んだ文を収集することで，コーパスを構築し，分析を行う．そして，収集した文を用いた感情推定実験を行い，考察する．
42.	Fuji Ren : Enriching Mental Engineering, 信学技報, Vol.NLC2010, No.12, 19-24, Oct. 2010. (Summary) A new academic system called "Enriching Mental Engineering" (EME) is presented. EME aims to deal with the mental of human being and to have some engineering methods for enriching mental. In this paper, the definition, research contents and the study method of EME will be described. A new concept about the measure of mental richness will be proposed and a Emotion Energy Function will be presented to estimate the external stimulus. The newest progress and future works of EME are also given in the paper.
43.	Motoyuki Suzuki, Tatsunori Okamatsu and Fuji Ren : On-set detection method of notes in singing voice based on tonal information, IPSJ SIG Technical Report, Vol.2010-MUS-85, No.9, 1-6, May 2010. (Summary) It is desirable that an Music Information Retrieval (MIR) system accepts a singing voice with lyrics as a retrieval key. In order to use a front-end of a Query-by-Singing MIR system, a new on-set detection method has been proposed. After detecting on-set frames by using power information, tonal intervals are calculated for all combinations of frames, and on-set frames are detected by using partial differential coefficients and its histogram. Experimental results showed the proposed method gave higher performance than the power-based method. F-value of the proposed method was 0.729, and f-value of the powerbased method was only 0.513.
44.	Katsura Yasushi, Kazuyuki Matsumoto and Fuji Ren : Expantion of Super-Function for Adjective to affect Noun, 情報処理学会全国大会講演論文集, Mar. 2010. (Summary) 本稿では，Super-Function(SF)に基づく機械翻訳を拡張するために，名詞にかかる形容詞を対象とした研究をおこなった．本研究で提案する手法は，名詞にかかる形容詞を名詞と合せて定数を減少させることで，重複したSFをデータベースから削除することで時間的・空間的コストを削減する． (Keyword) スーパー関数,機械翻訳
45.	Yoshioka Naoki, Kazuyuki Matsumoto and Fuji Ren : 英語科学技術論文執筆支援のための日英対訳例文データベース自動構築手法, 情報処理学会創立50周年(第72回)全国大会講演論文集, Mar. 2010. (Summary) 近年，英語科学技術論文の執筆の機会が分野を問わず増えている．本研究では，英語科学技術論文を執筆する際のサポートに用いることが可能な，日英対訳例文データベースの構築を目指す．このデータベースは，固有名詞や一般名詞などで，同一属性の語に置き換え可能な単語を，コーパスから学習した知識に基づき自動検出することで，それらの語の部分を変数として条件式に置換して構築される．本手法により構築した例文データベースは，論文作成支援のみならず，論文執筆の機会に乏しい大学生のための学習ツールへの応用にも有用と考えられる． (Keyword) 英作文支援,日英対訳データベース
46.	Ogawa Takuki, Kazuyuki Matsumoto and Fuji Ren : Emotion estimation for short sentence using word 1-gram as the feature, 情報処理学会創立50周年記念(第72回)全国大会講演論文集, Mar. 2010. (Summary) ユーザとの親和性の高い対話システムを実現するにはユーザの情緒面を考慮に入れて対応する必要がある．我々はユーザのつぶやきや一言からユーザの情緒を推定し，また，対話を始めるきっかけとすることでユーザの状態を考慮した自然な対話をおこなうエージェントを実現できると考える．しかし，つぶやきや一言に含まれる単語数は少なく，含まれる情報が少ないため感情推定が困難である．また，これまで短文に特化した感情推定手法は存在しない．本研究では，短文に含まれる単語や記号の持つ言語的意味と文章に表される感情との関係に着目し，単語1-gramを素性として，Webサービス「えもにゅ」に投稿された短文のコーパスを用いて統計的手法により感情推定をおこなう． (Keyword) 感情推定 / 単語N-gram / 単語1-gram
47.	Fuji Ren : 「豊心工学」学問体系の確立(1):ブログ情報に基づく感情状態解析, 情報処理学会全国大会講演論文集, No.3D-7, 2-51-2-52, Mar. 2010.
48.	Ling Xia and Fuji Ren : Research on Chinese Cuisine QA Service System, 情報処理学会全国大会講演論文集, No.B1-8, 67-69, Mar. 2010.
49.	Tatsuya Sato, Motoyuki Suzuki and Fuji Ren : オントロジーに基づく多様な発話に対応した対話システムの構築, 情報処理学会全国大会講演論文集, No.6X-5, Mar. 2010.
50.	Masashi Adachi, Motoyuki Suzuki and Fuji Ren : LSP係数の性質を考慮した音声符号化法の改善, 情報処理学会全国大会講演論文集, No.1U-1, Mar. 2010.
51.	Tatsunori Okamatsu, Motoyuki Suzuki and Fuji Ren : 音程変化に基づく歌唱中の音符区間検出, 情報処理学会全国大会講演論文集, No.5T-2, Mar. 2010.
52.	Takeshi Isawa, Fuji Ren and Motoyuki Suzuki : 感情の表出ができる学内案内ロボットの構築について, 情報処理学会全国大会講演論文集, No.1N-4, Mar. 2010.
53.	Kurihara Takeru, Kazuyuki Matsumoto, Seiji Tsuchiya and Fuji Ren : Semantic Analysis of Metaphor "A-no-B" based on Sememe, IPSJ SIG Technical Report, Vol.2010-NL-195, No.1, 1-6, Jan. 2010. (Summary) The metaphor expression is used in various scenes that treat the natural language like the newspaper articles and the daily conversation, etc. We can express our intention by using metaphor expressions. However, it is very difficult to analyze metaphor expression by a computer. This paper constructs two kind of metaphor dictionaries. We also analyze meaning of metaphor"A-no-B" by searching metaphor dictionaries. Using the method described in this paper, we showed that this method was able to analyze meaning of metaphor A-no-B" with accuracy about 70%. (Keyword) 比喩 / 隠喩 / 意味素 / AのB
54.	Takuki Ogawa, Kazuyuki Matsumoto and Fuji Ren : About emotion estimation of Emonyu short sentence, IPSJ SIG Technical Report, Vol.2010-NL-195, No.2, 1-6, Jan. 2010. (Summary) This paper proposes a SVM-based emotion estimation method from a short message or a word by using word 1-gram as feature and use contribution of "Emonyu" as a corpus. "Emonyu" is a web service to which users contribute a short message or a word with a emotion mark.Therefore, the corpus using"Emonyu"contribution enables reflect writer's emotion directly,and reduce work of adding emotion tags to sentences of corpus. We use word 1-gram as feature is,in short sentences like a short message or a word including a few features,a writer generally express emotion using a linguistic meaning of a word or a mark and it is necessary to reduce a number of kinds of feature to get exact appear frequency of features. The result of experiments show that the F-measure of proposed method is higher than the F-measure of method using word 2-gram as a feature in all emotions.
55.	Yuki Hashimoto, Motoyuki Suzuki and Fuji Ren : 新聞記事の意味解析における意味フレームの有効性についての考察, The 4th NLP Symposium for Young Researchers, Sep. 2009.
56.	YUHUA DING and Fuji Ren : Constructing Chinese Internet Terminology Corpus, IPSJ SIG Technical Report, NL, Vol.193, No.4, 1-7, Sep. 2009. (Summary) In recent years, internet widely used in the internet industry with a different form of the traditional languages i.e. internet terminology has been emerged. The internet terminology is very popular among young peoples, and it is used for self-expression. A few researchers have studied the Chinese internet terminology language processing but exact meaning of the words is not completely understood yet. Therefore an attempt has been made to build the corpus of Chinese internet terminology. In this paper, the Chinese internet terminology is divided into eight types based on the purpose, format, and source. We have carried out the analysis of the distribution of each category, and the psychology of young people reflected in the Chinese internet terminology.
57.	YUHUA DING and Fuji Ren : Constructing Chinese Internet Terminology Corpus, IPSJ SIG Technical Report, Vol.193, No.4, 1-7, Sep. 2009.
58.	Atsushi Sasaki, Motoyuki Suzuki and Fuji Ren : Analysis of Phoneme Recognition Characteristics of Multi-path Triphone, 日本音響学会研究発表会講演論文集, 1-2, Sep. 2009.
59.	Katsura Yasushi, Kazuyuki Matsumoto and Fuji Ren : Flexible English Composition by Negative-Positive Conversion, 電気学会電子·情報·システム部門大会論文集, 1513-1515, Sep. 2009. (Summary) With development of the recent globalization, the chance to exchange in English increased in the business eld Inparticular, it's necessary to write a thesis and a charter handwriting in English. Because many Japanese are not usedto the making of the English sentence, a burden is big without a thing such as the making assistance tool, and it isdicult to write an appropriate sentence in English. We have developed an English composition support system. Bythis system, It's to search for the interlinear translation example to refer to by database and generate a new sentence byreplacing a noun during the example sentence. In this paper, based on the technique of Super-Function, the techniqueof carrying out mutual conversion of an positive sentence and negative sentence is proposed, and enables more exibletext conversion. Conversion to a negative sentence from an positive sentence can be enabled by this technique, and canwiden width of the text conversion. (Keyword) English composition / composition support / Super-Function / negative sentence / mutual conversion
60.	吉岡伸浩, Kazuyuki Matsumoto and Fuji Ren : Detecting Cause of Authors Plesure by Blog Information Analysis, 電気学会電子·情報·システム部門大会論文集, 1446-1448, Sep. 2009. (Summary) Some people are writing blog now.Blog is often written by writers subjective idea, and there is a person whowrites his daily life, too.On the other hand,by work or personal relationships,stress by the over work,I become the depression and there is a person who writes sentences that hint the suicide to blog.Healing is needed in order to reduce the stress and worries of these people.However,healings to be pleased with by a person are different.Therefore,it is necessary to detect with what the writer is pleased.Therefore,in this paper,to propose methods,whether the writer of the blog is pleased to use N-gram frequency dictionary and emoticon and sign dictionary more than usual is judged and to detect the cause of the pleasure of the writer. (Keyword) weblog / pleasure / emotion
61.	Liping Wu and Fuji Ren : Multilingual Patent Retrieval based on Pragmatic Information, 電気学会電子·情報·システム部門大会論文集, 1475-1477, Sep. 2009.
62.	Yiruo Dai and Fuji Ren : Topic Selection and Professional Dictionary In Content-based Multilingual, 電気学会電子·情報·システム部門大会論文集, 1472-1474, Sep. 2009.
63.	Caixia Yuan and Fuji Ren : Using Function Tags to Recognize Opinion Elements, 電気学会電子·情報·システム部門大会論文集, 1462-1466, Sep. 2009.
64.	Xiaodong Liu and Fuji Ren : An Approach to Reduce Noise in CSS-based Chinese HTML Pages, 電気学会電子·情報·システム部門大会論文集, 1459-1461, Sep. 2009.
65.	Min Kyu and Fuji Ren : Link Detection Task Algorithms Review and User Interface in WEB3.0, 電気学会電子·情報·システム部門大会論文集, 1451-1453, Sep. 2009.
66.	Ling Xia and Fuji Ren : Query Expansion Using Domain Features, 電気学会電子·情報·システム部門大会論文集, 1449-1450, Sep. 2009.
67.	陳蕾 and Fuji Ren : 副詞および副詞に共起するフレーズの感情表現について, 電気学会電子·情報·システム部門大会論文集, 1444-1445, Sep. 2009.
68.	沐榕, 全昌勤 and Fuji Ren : 中国語接続詞に基づく感情表現分析, 電気学会電子·情報·システム部門大会論文集, 1441-1443, Sep. 2009.
69.	Ji Li and Fuji Ren : Constructing a Chinese Emotion Ontology with Tag of Emotion Intensity, 電気学会電子·情報·システム部門大会論文集, 1437-1440, Sep. 2009.
70.	Changqin Quan and Fuji Ren : Recognizing Sentence emotion based on Ren-CECps, 電気学会電子·情報·システム部門大会論文集, 1434-1436, Sep. 2009.
71.	Huana Li and Fuji Ren : Establishing a three-dimensional emotional space model based on Emotion Corpus, 電気学会電子·情報·システム部門大会論文集, 1431-1433, Sep. 2009.
72.	Wang Cheng, Fuji Ren and Changqin Quan : Corpus-based automatic classification of emotional expectation, 電気学会電子·情報·システム部門大会論文集, 1429-1430, Sep. 2009.
73.	堵子梁, 全昌勤 and Fuji Ren : 中国語感情コーパスに基づく感情主題句の自動抽出, 電気学会電子·情報·システム部門大会論文集, 1426-1428, Sep. 2009.
74.	Yan Sun, Changqin Quan and Fuji Ren : Analysis on Degree Words for Chinese Emotion Expressions, 電気学会電子·情報·システム部門大会論文集, 1423-1425, Sep. 2009.
75.	Ye Liu and Fuji Ren : Answer Generation based on Online Source for Japanese Guidance QA system, 電気学会電子·情報·システム部門大会論文集, 1421-1422, Sep. 2009.
76.	佐藤達也 and Fuji Ren : DODDLE-OWLを活かしたオントロジーの自動構築について, 電気学会電子·情報·システム部門大会論文集, 1416-1417, Sep. 2009.
77.	栗原健, Fuji Ren and Seiji Tsuchiya : 意味素の関連を考慮した隠喩の名詞句"AのB"の意味推定, 電気学会電子·情報·システム部門大会論文集, 1408-1411, Sep. 2009.
78.	Yuanlu Fu, Fuji Ren and Xiao Sun : Translation of Chinese Phrases in Super-Function based Chinese-Japanese Machine Translation, 電気学会電子·情報·システム部門大会論文集, 1372-1374, Sep. 2009.
79.	三品賢一 and Fuji Ren : 敬語表現とモダリティを考慮した発話役割同定, 電気学会電子·情報·システム部門大会論文集, 1367-1369, Sep. 2009.
80.	平尾卓也 and Fuji Ren : 自由発話できる雑談を目的とした発話役割同定について, 電気学会電子·情報·システム部門大会論文集, 1365-1366, Sep. 2009.
81.	袴田愛 and Fuji Ren : 会話中に登場する人物と発話者との人間関係推定, 電気学会電子·情報·システム部門大会論文集, 1363-1364, Sep. 2009.
82.	Guodong Zhang and Fuji Ren : New Word Identification by Word Fragment Features based on SVM, 電気学会電子·情報·システム部門大会論文集, 1392-1394, Sep. 2009.
83.	Fang Tian and Fuji Ren : Using Coordinate to Improve Hyponymy Acquisition for Chinese, 電気学会電子·情報·システム部門大会論文集, 1390-1391, Sep. 2009.
84.	Kaiyan Huang and Fuji Ren : Learning Lexical Pattern for Chinese Separable Verb-object Words, 電気学会電子·情報·システム部門大会論文集, 1385-1389, Sep. 2009.
85.	Lei Yu, Xiao Sun and Fuji Ren : Chinese Word Segmentation based on Conditional Random Field, 電気学会電子·情報·システム部門大会論文集, 1383-1384, Sep. 2009.
86.	Xiao Sun and Fuji Ren : CHINESE BASE PHRASES CHUNKING BASED ON LDCRF, 電気学会電子·情報·システム部門大会論文集, 1381-1382, Sep. 2009.
87.	Deyuan Qui and Fuji Ren : Chinese Name Entity Recognition based on Machine Learning, 電気学会電子·情報·システム部門大会論文集, 1378-1380, Sep. 2009.
88.	Liping Mi and Fuji Ren : Comparisons of Picture-word and Word Recognition Memory Characteristics, 電気学会電子·情報·システム部門大会論文集, 1227-1230, Sep. 2009.
89.	Yuki Hashimoto, Motoyuki Suzuki and Fuji Ren : 日本語フレームネットを用いた新聞記事の要点抽出, 電気学会電子·情報·システム部門大会論文集, 1418-1420, Sep. 2009.
90.	Hayato Shibuya, Motoyuki Suzuki, Seiji Tsuchiya and Fuji Ren : オノマトペデータベースを用いた未知のオノマトペの印象推定手法, 電気学会電子·情報·システム部門大会論文集, 1412-1415, Sep. 2009.
91.	Jia Ma, Motoyuki Suzuki and Fuji Ren : DETECT AND RECOGNIZE THE POSSIBLE SPOKESPERSON WITH CAMERA, IN A ROBOT-HUMAN COMMUNICATION SYSTEM, 電気学会電子·情報·システム部門大会論文集, 1342-1344, Sep. 2009.
92.	Hong Zhang, Motoyuki Suzuki and Fuji Ren : 日中機械翻訳における存在否定文の翻訳処理の問題について, 電気学会電子·情報·システム部門大会論文集, 1375-1377, Sep. 2009.
93.	Golam Mohammad Sohrab, Abdel Mohamed Fattah, Motoyuki Suzuki and Fuji Ren : Supervised Learning Technique using TF-IDF for Text Classification, 電気学会電子·情報·システム部門大会論文集, 1395-1398, Sep. 2009.
94.	Tatsunori Okamatsu, Motoyuki Suzuki and Fuji Ren : フレーム間の相互相関関数を用いた歌唱中の音符の区切り推定, 電気学会電子·情報·システム部門大会論文集, 734-736, Sep. 2009.
95.	Masashi Adachi, Motoyuki Suzuki and Fuji Ren : ML-BEATS法を用いたLSP係数のセグメント量子化法の検討, 電気学会電子·情報·システム部門大会論文集, 723-725, Sep. 2009.
96.	楊曄, 姜沛林, Seiji Tsuchiya and Fuji Ren : 語用論に基づく「論語」検索システムの構築, FIT2008(第7 回情報科学技術フォーラム), Vol.E, 213-214, Sep. 2008.
97.	jia Ma, Motoyuki Suzuki and Fuji Ren : Robot System for Recognizing the Speakers and Their Expressions with Image Processing, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 431, Sep. 2008.
98.	Peilin Jiang, Motoyuki Suzuki and Fuji Ren : Visual Feature Extraction from Web Page based on Attention Model, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 432, Sep. 2008.
99.	源祐輔, Motoyuki Suzuki and Fuji Ren : 表情の強さを制御した表情動画データベースの構築, 平成20年度電気関係学会四国支部連合大会論文集, 200, Sep. 2008. (Keyword) キーワード分類
100.	前田健吾, Motoyuki Suzuki and Fuji Ren : ロボットへの動作教示システムのための単眼視と両眼視による特徴点抽出法の比較, 平成20年度電気関係学会四国支部連合大会論文集, 189, Sep. 2008. (Keyword) キーワード分類
101.	深海正裕, Motoyuki Suzuki and Fuji Ren : 韻律情報のみから伝わる感情の調査, 平成20年度電気関係学会四国支部連合大会論文集, 198, Sep. 2008. (Keyword) キーワード分類
102.	佐々木敦史, Motoyuki Suzuki and Fuji Ren : 韻律情報のみから伝わる感情の調査, 平成20年度電気関係学会四国支部連合大会論文集, 287, Sep. 2008. (Keyword) キーワード分類
103.	喜多雅彦, Motoyuki Suzuki and Fuji Ren : 多数話者内での順位情報を用いた話者照合法における耐雑音性の評価, 平成20年度電気関係学会四国支部連合大会論文集, 286, Sep. 2008. (Keyword) キーワード分類
104.	岡松竜徳, Motoyuki Suzuki and Fuji Ren : 歌唱による音楽検索システムにおけるLPC 残差信号を用いた音程特徴量の抽出, 平成20年度電気関係学会四国支部連合大会論文集, 285, Sep. 2008. (Keyword) 自然言語処理 / 英作文支援 / キーワード分類
105.	張紅 and Fuji Ren : 日中機械翻訳における否定「ナイデ」と「ナクテ」の処理手法, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 283, Sep. 2008.
106.	Guodong Zhang and Fuji Ren : A method of Chinese New Word Identification based on Repeated String, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 419, Sep. 2008.
107.	Caixia Yuan and Fuji Ren : Predicate-Argument Annotating for Unparsed Text, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 417, Sep. 2008.
108.	Ye Wu and Fuji Ren : Emotion Recognition for Chinese Negative Sentences, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 426, Sep. 2008.
109.	Fang Tian and Fuji Ren : Extraction of Relation instances for Domain Ontology from the Web, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 284, Sep. 2008.
110.	Xiao Sun and Fuji Ren : Hidden semi-CRF for Chinese New Words Detection and POS Tagging, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 318, Sep. 2008.
111.	Changqin Quan and Fuji Ren : Sentimental Classification Based on Kernel Methods, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 425, Sep. 2008.
112.	Deyuan Qiu and Fuji Ren : A Study on Chinese Person Name Recognition, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 420, Sep. 2008.
113.	Ibrahim Nagwa, Fattah Abdel Mohamed and Fuji Ren : The integration of ICT into Schools in Tokushima City - Japan, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 435, Sep. 2008.
114.	Begum Nadira, Fattah Abdel Mohamed and Fuji Ren : Bengali text Summarization Using Hidden Markov Model, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 423, Sep. 2008.
115.	Sohrab Golam Mohammad, Fattah Abdel Mohamed and Fuji Ren : Single-Document extraction based Automatic Text Summarization and evaluation technique, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 422, Sep. 2008.
116.	Liping Mi and Fuji Ren : A comparison of Japanese recognition process between CJL and JNS, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 428, Sep. 2008.
117.	Tianjiao Gu and Fuji Ren : Fuzzy Set based Question Matching in Question Answer System, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 434, Sep. 2008.
118.	Liu Ye, Teng Zhi, Seiji Tsuchiya and Fuji Ren : Method of Japanese Unknown Placename Detection based on Support Vector Machine, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 416, Sep. 2008.
119.	Li Ji, Seiji Tsuchiya and Fuji Ren : Affect Sensing for Web Blog, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 429, Sep. 2008.
120.	Mishina Kenichi, Seiji Tsuchiya and Fuji Ren : An Emotion Recognition using Smoothing Word N-gram Frequency, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 427, Sep. 2008.
121.	Hakamata Ai, Seiji Tsuchiya and Fuji Ren : Expression Generation Method based on Discourse and Discourse Intention, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 430, Sep. 2008.
122.	SHINOMIYA Mizuho, Seiji Tsuchiya and Fuji Ren : An Approach of Article's Opinion Classification based on Word Information, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 424, Sep. 2008.
123.	吉岡伸浩, Seiji Tsuchiya and Fuji Ren : 単語の感情属性と文の位置情報に基づくblogの感情推定, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 268, Sep. 2008.
124.	湯浅隆運, Seiji Tsuchiya and Fuji Ren : 会話者の感情相違を利用した場の雰囲気の推定, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 269, Sep. 2008.
125.	平尾卓也, Seiji Tsuchiya and Fuji Ren : インタラクティブな会話システムにおける質問文の生成, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 271, Sep. 2008.
126.	渋谷隼人, Seiji Tsuchiya and Fuji Ren : 未知のオノマトペからの印象推定手法, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 266, Sep. 2008.
127.	佐藤達也, Seiji Tsuchiya and Fuji Ren : 対話コンテンツ作成のための単語間の関係抽出, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 267, Sep. 2008.
128.	栗原健, Seiji Tsuchiya and Fuji Ren : 意味素とシソーラスに基づく名詞句「AのB」の意味推定, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 265, Sep. 2008.
129.	川島宏文, Seiji Tsuchiya and Fuji Ren : 段階的クエリ拡張によるWhy 型質問応答手法の提案, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 272, Sep. 2008.
130.	井澤健, Seiji Tsuchiya and Fuji Ren : 音声認識の誤認識に頑健な質問文検索手法, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 317, Sep. 2008.
131.	足立征士, Seiji Tsuchiya and Fuji Ren : 聞き手の感情生起に韻律的特徴が及ぼす影響の分析, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 270, Sep. 2008.
132.	Xia Ling, Kazuyuki Matsumoto and Fuji Ren : Question Classification in Chinese Cuisine QA System, 平成20年度電気関係学会四国支部連合大会論文集, 433, Sep. 2008. (Summary) This paper presents an integrated method on question classification for Chinese cuisine question answering (QA) system. First, we exploit the domain knowledge to enrich question preprocessing, then classification features are extracted by means of domain attributes and the rule-based classifier is constructed. Support vector machine (SVM) classifier is used for secondary classification to the questions which cannot be matched with rules. A prototype system based on the proposed method has been constructed and an experiment on 453 natural language questions collected from Internet has been carried out. It achieved an accuracy of 96.22%. Result shows that a small number of linguistically motivated domain features can efficiently classify questions of Chinese cuisine QA system. (Keyword) QA system
133.	Kazuyuki Matsumoto and Fuji Ren : Construction of User-Oriented Intelligent English Composition Support System, 平成20年度電気関係学会四国支部連合大会論文集, 313, Sep. 2008. (Summary) 本研究では，スーパー関数を応用した知的英作文支援システムを構築する．利用者がベースとなる英文テンプレートを選ぶとき，利用者の検索意図に合致したものが出力できるように，キーワードの自動付与と，スーパー関数による日英対訳対応付け方法による例文提示手法を用いる．なお，提案システムは，利用者の記憶を辿りやすくするため，英文検索履歴や英文作成履歴を登録し，選択した訳語の選択履歴を時系列順に保持することで，まさに今作成しようとしている英文を書くための支援を可能とする． (Keyword) 英作文支援
134.	Tanimoto Yuki, Kazuyuki Matsumoto and Fuji Ren : Collection and analysis of Japanese-English idiomatic expression for construction of English composition support system, 平成20年度電気関係学会四国支部連合大会論文集, 282, Sep. 2008. (Summary) 本研究では，英作文支援システムにおいて，よく利用されるであろう慣用表現の用例をデータベース化し，その有効性について分析をおこなう．日英の対訳慣用表現辞書は，一般に，一方の言語のみを知っているだけでは，その使い道が分かりづらい点がある．そのため，対訳関係を登録しておくだけでなく，意味や感情といった，慣用表現自体が持つ役割をデータベースに登録しておくことで，より簡便で直感的な検索を実現することを目的としている． (Keyword) 慣用表現 / 英作文支援 / 日英慣用表現
135.	Katsura Yasushi, Kazuyuki Matsumoto and Fuji Ren : Japanese-English Bilingual Database Construction in English Composition Support System, 平成20年度電気関係学会四国支部連合大会論文集, 314, Sep. 2008. (Summary) 本研究では，英作文支援システムにおける日英対訳データベースを構築するための手法について提案する．我々の提案する英作文支援システムは，ユーザが書きたい英文のテンプレートをテーマ別に登録したテンプレートデータベースを参照し，その例文を手作業で編集していくシステムである．本システムの核となる技術として，スーパー関数形式によるテンプレートの自動登録手法と，スーパー関数内の訳語の自動推薦手法がある．本稿では，これらの技術を実現するために必要な要素を日英対訳テンプレートに登録するための手法について述べる． (Keyword) Super-Function / 英作文支援 / 日英対訳データベース
136.	Aoki Yui, Kazuyuki Matsumoto and Fuji Ren : Keyword automatic classification in the English composition support system, 平成20年度電気関係学会四国支部連合大会論文集, 281, Sep. 2008. (Summary) 本研究では，英作文支援システムにおけるキーワードの自動分類をおこなうため，ルールベースの手法を提案する．キーワードに関連付けられた複数のサブキーワードの集合から，ひとつのキーワードを選定するために，キーワードとカテゴリ間の関連付けを人手によりおこない，この関連付けに基づき，階層的な構造をもつカテゴリのなかから，キーワードのカテゴリのパスを1つに定める． (Keyword) 自然言語処理 / 英作文支援 / キーワード分類
137.	Kazuyuki Matsumoto, Junko Minato, Seiji Tsuchiya and Fuji Ren : 日英対訳感情表現コーパスに基づく感情表現抽出手法の提案, IPSJ SIG Technical Report, Vol.2008, No.NL-184, 69-75, Mar. 2008. (Summary) This paper statistically studies the emotional features of Japanese and English based on an emotion annotated parallel corpus and proposes a method for extracting emotional expressions. The proposed method estimates the emotion category of the emotional expressions by focusing on the three kinds of features: part of speech of emotional expression, position of emotional expression and part of speech of the previous/next morpheme of the target emotional expression. The evaluation experiment resulted over 90.0% (joy, hate) of accuracy in the method based on part of speech features. (Keyword) Sensibility information processing / Emotion tagged parallel corpus
138.	Ibrahim Nagwa, Fuji Ren, Shingo Kuroiwa, Ryosuke Sumitomo and Seiji Tsuchiya : Obstacles at Integration of Schools into ICT as regard to the Opinions of the Teachers and Administrators of Schools in Tokushima, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 377, Sep. 2007.
139.	Sohrab golam Mohammad, Fuji Ren, Shingo Kuroiwa, Ryosuke Sumitomo and Seiji Tsuchiya : Super-Function based English to Bengali Machine Translation, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 376, Sep. 2007.
140.	Sasayama Manabu, Fuji Ren, Shingo Kuroiwa, Seiji Tsuchiya and Ryosuke Sumitomo : Super-Function based machine translation using concept of words, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 375, Sep. 2007.
141.	Yin Dapeng, Shao Min, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : The hybrid strategy processing approach of Chinese complex long sentenct in Chinese-Japanese machine translation, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 374, Sep. 2007.
142.	Shinomiya Mizuho, Fuji Ren, Shingo Kuroiwa, Ryosuke Sumitomo and Seiji Tsuchiya : An approach of extracting the opinion based on the emotion words, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 373, Sep. 2007.
143.	Zhang Guodong, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : A Study on Text Summarization Based on Statistic Features, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 372, Sep. 2007.
144.	Yang Ye, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : Document Retrieval Based on the Pragmatics Information, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 371, Sep. 2007.
145.	Li Yun, Huang Kaiyan, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : Similar Word Association and Integration Based on WikiPedia Semantic Classification, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 370, Sep. 2007.
146.	Liu Song, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : The structure of the knowledge base of Confucius, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 368, Sep. 2007.
147.	Zhi Teng, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : Multimedia Applications in Conversation System, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 367, Sep. 2007.
148.	Xia Ling, Tian Fang, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : Corpus Feature Analysis for Sichuan Cuisine QA System, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 366, Sep. 2007.
149.	Tian Fang, Xia Ling, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : Ontology Construction of Chinese Festivals, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 365, Sep. 2007.
150.	Kyoko Osaka, Tetsuya Tanioka, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa, Shu-ichi Ueno and Fuji Ren : Spectrogram based on empathic understanding, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 364, Sep. 2007.
151.	Jiang Peilin, Fuji Ren, Shingo Kuroiwa, Seiji Tsuchiya and Ryosuke Sumitomo : Speak Detection in Image Sequences, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 362, Sep. 2007.
152.	Yu Lei, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : A Study on Text Orientation Identification Based on SVM, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 361, Sep. 2007.
153.	Mi Liping, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : A study on the role of Chinese character and pictures in the learning, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 360, Sep. 2007.
154.	山本麻由, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : 感情タグつきコーパスの構築についての一考察, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 330, Sep. 2007.
155.	袴田愛, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : 心的状態遷移ネットワークに基づく表情生成手法, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 329, Sep. 2007.
156.	劉曄, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : 構文解析に基づく類似度計算, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 328, Sep. 2007.
157.	竹内公紀, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : デザインの評価に特化した特徴量抽出法の検討, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 310, Sep. 2007.
158.	米麗英, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : 日中機械翻訳における使役表現の処理, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 287, Sep. 2007.
159.	小西優輔, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : 日本語学習者のための日本語慣用句学習支援システムの構築, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 286, Sep. 2007.
160.	湯浅隆運, Fuji Ren, Shingo Kuroiwa, Seiji Tsuchiya and Ryosuke Sumitomo : 感情推定における発話者と聞き手の感情相違の利用についての一考察, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 285, Sep. 2007.
161.	足立征士, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : 単語表記と音声から生起される感情の違いについての考察, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 284, Sep. 2007.
162.	Kazuyuki Matsumoto, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : 感情表現主体判定に基づく話者感情推定, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 283, Sep. 2007. (Summary) 本研究では，複数話者間における会話からの感情推定において重要となる，感情表現主体の判定手法を提案する．感情は一般的には，対人感情と自我感情に分けることができるが，それらの感情の判別には，発話文の主語が何であるかが重要となる．本研究は，人称代名詞に着目し，人称代名詞の種類別に感情が誰に生起しているか，誰に対しての感情であるかを判別することを目的とする．
163.	三品賢一, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : 感情辞書を用いた感情類似度計算手法, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 282, Sep. 2007.
164.	山田大地, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : N-gramを用いた顔文字の表情分類手法, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 281, Sep. 2007.
165.	喜多雅彦, Satoru Tsuge, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : 多数話者内での順位情報を用いた話者照合, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 280, Sep. 2007.
166.	大林克行, Satoru Tsuge, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : 音素毎の話者識別性能の調査, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 279, Sep. 2007.
167.	井澤健, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : 音声対話情報案内システムにおける質問文検索手法について, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 278, Sep. 2007.
168.	佐藤達也, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : 知的案内システムにおけるコンテンツ収集について, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 277, Sep. 2007.
169.	久積克年, Fuji Ren, Shingo Kuroiwa, Seiji Tsuchiya and Ryosuke Sumitomo : 視点を考慮した明示的な関係の抽出について, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 276, Sep. 2007.
170.	渋谷隼人, Fuji Ren, Shingo Kuroiwa, Ryosuke Sumitomo and Seiji Tsuchiya : ユーザの嗜好に着目したWEBサイト構築支援について, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 248, Sep. 2007.
171.	源祐輔, Fuji Ren, Shingo Kuroiwa, Ryosuke Sumitomo and Seiji Tsuchiya : 人物特質性と顔表情の関連性について, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 191, Sep. 2007.
172.	那琳, Fuji Ren, Shingo Kuroiwa, Seiji Tsuchiya and Ryosuke Sumitomo : 局部特徴に基づく顔識別, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 190, Sep. 2007.
173.	高橋新之介, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : 感情認識のための顔表情DBの構築について, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 189, Sep. 2007.
174.	馬嘉, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : 表情認識システムの新しい画像処理方法, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 188, Sep. 2007.
175.	川島宏文, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : 対話型案内コンテンツを用いた学習の有効性評価, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 187, Sep. 2007.
176.	平井孝則, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : 突発性雑音に頑健な音声認識の為の繰り返し発声を用いた音声強調法, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 154, Sep. 2007.
177.	佐野貴彦, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : 感情情報を用いた日本語慣用句教授学習システムの研究, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 7, Sep. 2007.
178.	Satoru Tsuge, Shingo Kuroiwa, 喜多雅彦, 蒔苗久則, 長内隆, 鎌田敏明, 谷本益巳, Minoru Fukumi and Fuji Ren : Speaker identification experiment using a large Japanese speech corpus, 日本音響学会秋季研究発表会, 97-98, Sep. 2007.
179.	蒔苗久則, 長内隆, 鎌田敏明, 谷本益巳, Satoru Tsuge, Shingo Kuroiwa and Fuji Ren : A study on the influence of the utterance content of bone-conducted speech into speaker verification, 日本音響学会秋季研究発表会, 97-98, Sep. 2007.
180.	楊曄, Kazuyuki Matsumoto, 劉松, Fuji Ren and Shingo Kuroiwa : 語用情報に基づく『論語』の質問応答システムに関する研究, 言語処理学会第13回年次大会, 1010-1013, Mar. 2007. (Summary) 我々は，『論語』に関する単なる全文検索システムではなく，『論語』の内容検索を支援するシステムを開発している．本論文では，『論語』の言語表現の特徴に応じて，語用情報とカテゴリに基づく検索手法を提案した．抽出したカテゴリは，大分類と小分類がある．大分類は学習，教育,友，治国，教養など17種類ある．また，既存の『論語』関連サイトや著作を参考し，語用情報を抽出した．本システムを用いると，ユーザの質問に対し，『論語』からの適切な文章が返される． (Keyword) 論語 / 語用情報 / カテゴリ / 質問応答
181.	Satoru Tsuge, 清田啓二, Masami Shishibori, Kenji Kita, Fuji Ren, Minoru Fukumi and Shingo Kuroiwa : Analysis of Variation on Intra-Speaker's Speech Recognition Performances, 日本音響学会春季研究発表会, 165-166, Mar. 2007.
182.	喜多雅彦, Satoru Tsuge, Fuji Ren and Shingo Kuroiwa : Speaker verification based on rank information using many speaker models, 日本音響学会春季研究発表会, 161-162, Mar. 2007.
183.	高階政吏, Satoru Tsuge, Fuji Ren and Shingo Kuroiwa : Speech Bandwidth Extension Method using Speech Recognition, 日本音響学会春季研究発表会, 297-298, Mar. 2007.
184.	Satoru Tsuge, 清田啓二, Masami Shishibori, Kenji Kita, Fuji Ren, Minoru Fukumi and Shingo Kuroiwa : Analysis of Variation on Intra-Speaker's Speech Recognition Performances, 日本音響学会春季研究発表会, 165-166, Mar. 2007.
185.	光吉俊二, 田中靖人, 柴崎晃一, Fuji Ren and Shingo Kuroiwa : 韻律情報に基づく自然感情の認識システムによる脳情動研究, Brain Communication研究会, 33-43, Sep. 2006. (Keyword) QA system
186.	Satoru Tsuge, 小澤光広, Masami Shishibori, Minoru Fukumi, Fuji Ren, Kenji Kita and Shingo Kuroiwa : A Japanese Specific Speakers' Corpus Long Period, 日本音響学会2006年秋季研究発表会, 277-278, Sep. 2006.
187.	Fuji Ren : Recognizing Human Emotion based on appearance information and Mental State Transition Network, 情報処理学会研究会報告, Vol.2006, No.73, 43-48, Sep. 2006. (Summary) Many people still seem to have strong resistance toward interacting with machines in many business fields such as terminal devices and medical care systems. We focus on human psychological characteristics to develop general-purpose agents that can recognize human emotion and create machine emotion. We comprehensively analyze brain waves, voice sounds and picture images that represent information included in emotion elements of phonation, facial expressions, and speech usage. We analyze and estimate many statistical data based on the latest achievements of brain science and psychology in order to derive transition networks for human psychological states. We establish a speaker word model for researching computer simulation of psychological change and emotional presentation, developing emotion interface, and establishing theoretic structure and realization method of emotion communication. In the talk, a new approach for recognizing human emotion based on appearance information and Mental State Transition Network will be described and some new results for the project will be given.
188.	大坂京子, Tetsuya Tanioka, Chiemi Kawanishi, Toshiko Tada, Fuji Ren and 小林春男 : 人の感情変化と脳波活動電位量の変化との関連, 日本看護福祉学会誌, Vol.12, No.1, 50-51, Jul. 2006.
189.	Satoru Tsuge, Masami Shishibori, Fuji Ren, Kenji Kita and Shingo Kuroiwa : Investigation on variability of performance on speaker depend speech recognition, 日本音響学会春季研究発表会, 157-158, Mar. 2006.
190.	Satoru Tsuge, Masami Shishibori, Fuji Ren, Kenji Kita and Shingo Kuroiwa : A study of the suppression method of speech recognition performance against the utterance variation on the long and short period in a speaker, 日本音響学会春季研究発表会, 221-222, Sep. 2005.
191.	Satoru Tsuge, Yoshiyuki Umeda, Fuji Ren and Shingo Kuroiwa : A Study of Distributed Speaker Recognition Method using Vector Quantization and Earth Mover's Distance, 日本音響学会春季研究発表会, 17-18, Mar. 2005.
192.	Satoru Tsuge, Masami Shishibori, Kenji Kita, Fuji Ren and Shingo Kuroiwa : A study of the utterance variation on the long and short period in a speaker, 日本音響学会春季研究発表会, 129-130, Mar. 2005.
193.	胡海青, Fuji Ren, Shingo Kuroiwa and 張樹武 : 中国語文型の特徴を利用した観光質問応答システムの構築, 言語処理学会第11回年次大会, Vol.D5-4, 1080-1083, Mar. 2005.
194.	顔加軍, 姜沛林, Shingo Kuroiwa and Fuji Ren : 複合語構成規則を用いた意味解析, 言語処理学会第11回年次大会, Vol.C5-1, 1036-1039, Mar. 2005.
195.	Mohamed Abdel Fattah, Fuji Ren and Shingo Kuroiwa : Speaker Recognition for DSR, 言語処理学会第11回年次大会, Vol.D4-3, 934-937, Mar. 2005.
196.	金珍玉, Fuji Ren and Shingo Kuroiwa : 中韓機械翻訳におけるスーパー関数の構築について, 言語処理学会第11回年次大会, Vol.A4-4, 558-855, Mar. 2005.
197.	Mohamed Abdel Fattah, Fuji Ren and Shingo Kuroiwa : Use of Stemming for Information Retrieval, 言語処理学会第11回年次大会, Vol.B3-4, 562-565, Mar. 2005.
198.	尹大鵬, 邵敏, Fuji Ren and Shingo Kuroiwa : 統計情報と構文知識を利用した「把」文型の翻訳手法, 言語処理学会第11回年次大会, Vol.A3-8, 542-545, Mar. 2005.
199.	邵敏, 尹大鵬, Fuji Ren and Shingo Kuroiwa : 中日数量詞の機械翻訳規制を開発するための調査分析, 言語処理学会第11回年次大会, Vol.A3-2, 518-521, Mar. 2005.
200.	Qiong Liu, Fuji Ren, Xin Lu and Shingo Kuroiwa : From Knowledge to Linguistic Expression -A Novel Stock Market Expert System using Extended Super-Function, 言語処理学会第11回年次大会, Vol.A2-2, 348-351, Mar. 2005.
201.	張羽, Fuji Ren and Shingo Kuroiwa : 中国語感性処理における感性辞書の構築, 言語処理学会第11回年次大会, Vol.S1-7, 148-165, Mar. 2005.
202.	Kazuyuki Matsumoto, Fuji Ren and Shingo Kuroiwa : 語の意味情報を考慮した感情推定アルゴリズム, 言語処理学会第11回年次大会, Vol.S1-2, 145-148, Mar. 2005. (Summary) It is an indispensable point to recognize and extract the information in human sensitivities(sound, face expressions, and emotions) to actualize the communication without any sense ofincongruity with human. In our research group, though the research on the sensible computerconstruction has been carried out as an attempt to make the computer have the warmheartnessor kindness that are special to human, for the present, the research on the feeling estimationfrom the human conversation sentences is in practice as the fundamental research for theconstruction of welfare robot with sensitivities that support the lives of elders and reducethe caring burden. In this paper, we proposed the emotion estimation algorithm from theconversation sentences based on the attribute of word. (Keyword) conversation / welfare robots / natural language processing / sensibility
203.	Yusuke Konishi, Fuji Ren and Shingo Kuroiwa : 自然言語処理技術を用いた中学理科教授学習システム, 言語処理学会第11回年次大会, Vol.D1-8, 133-136, Mar. 2005.
204.	Satoru Tsuge, Yoshiyuki Umeda, Fuji Ren and Shingo Kuroiwa : Distributed Speaker Recognition using Earth Mover's Distance, 日本音響学会秋季研究発表会, 91-92, Sep. 2004.
205.	Satoru Tsuge, Youji Mori, Fuji Ren and Shingo Kuroiwa : Wind Noise Reduction Method with Multiple Noise Models, 日本音響学会秋季研究発表会, 723-724, Sep. 2004.
206.	Ippei Fukuda, Satoru Tsuge, Fuji Ren and Shingo Kuroiwa : A speaker recognition using ETSI standard DSR front-end, 日本音響学会春季研究発表会, 175-176, Mar. 2004.
207.	Kouji Tanaka, Shingo Kuroiwa, Satoru Tsuge and Fuji Ren : An acoustic model adaptation using HMM-based speech synthesis, 情報科学技術フォーラム(FIT)2003, 251-252, Sep. 2003.
208.	Kouji Tanaka, Satoru Tsuge, Fuji Ren and Shingo Kuroiwa : An acoustic model adaptation using HMM-based speech synthesis, 日本音響学会秋季研究発表会, 133-134, Sep. 2003.
209.	Kuniyoshi Kobayashi, Satoru Tsuge, Fuji Ren and Shingo Kuroiwa : An Evaluation of Packet Loss Concealment Algorithm using Speech Recognition and Synthesis, 日本音響学会秋季研究発表会, 321-322, Sep. 2003. (Summary) 近年のVoIP技術発展に伴い，IP電話が急速に普及しつつある． IP電話の本質的な問題として(特に無線区間がある場合)，パケット損失による音声品質の劣化が挙げられる．長い区間の音声途切れ及び複数音素の欠落に対処する手法として音声認識·音声合成を用いた音声途切れ補間手法を提案した．本稿では，特定女性話者モデルを用いて主観評価実験及び客観評価実験を行い，提案手法の有効性を示す．
210.	Kazuyuki Matsumoto, Shingo Kuroiwa and Fuji Ren : About the emotion measurement system, IEICE Technical Report, Vol.103, No.114, 55-60, Jun. 2003. (Summary) It is necessary to nurse the senior citizen for declining population of children and increasing nuclear family. We are researching and developing a welfare robot which has a sensibility to support the life of the senior citizen and to reduce nursing. One of the basic researches on such welfare robots is to measure the sensibility from conversation sentences, In this paper, an algorithm for measuring the sensibility is presented, and a prototype system based on the proposed algorithm has been constructed. (Keyword) conversation / welfare robot / natural language processing
211.	Kuniyoshi Kobayashi, Satoru Tsuge, Fuji Ren and Shingo Kuroiwa : A Packet Loss Concealment Algorithm using Speech Recognition and Synthesis, 日本音響学会春季研究発表会, 179-180, Mar. 2003. (Summary) 近年のVoIP技術発展に伴い，IP電話が急速に普及しつつある． IP電話の本質的な問題として(特に無線区間がある場合)，パケット損失による音声品質の劣化が挙げられる．この問題を解決する手法として，G711 Appendix Iが利用されている．しかし，この手法は長い区間の音声途切れ及び複数音素の欠落に対応していない．そこで，この問題を解決するために，音声認識·音声合成を用いた音声途切れ補間手法を提案した．
212.	Kazuyuki Matsumoto, Fuji Ren and Shingo Kuroiwa : 感性コンピュータの基礎研究ーその1:感性情報処理の現状，問題と展望ー, 平成14年度電気関連学会四国支部連合大会, 280, Oct. 2002. (Summary) 本研究では，人間の感性を理解するコンピュータ「感性コンピュータ」を実現するために何が必要か，そして，現時点での問題点について考察する．
213.	Tadashi Shoda, Yusuke Konishi, Fuji Ren and Shingo Kuroiwa : 自然言語処理技術を用いた中学理科教授学習システム構想, 電気関連学会四国支部連合大会, 279, Oct. 2002.
214.	森崎悠子, Fuji Ren and Shingo Kuroiwa : 文脈情報を利用した会話文における人物の感情計測, 電気関連学会四国支部連合大会, 278, Oct. 2002.
215.	Yusuke Konishi, Tadashi Shoda, Fuji Ren and Shingo Kuroiwa : 中学理科の教師協調教育支援システムについて, 電気関連学会四国支部連合大会, 277, Oct. 2002.
216.	Satoru Tsuge, Shingo Kuroiwa, Fuji Ren and Kenji Kita : ETSI標準分散音声認識フロントエンドを用いた音声認識実験, 日本音響学会春季研究発表会, 171-172, Mar. 2002.
217.	Satoru Tsuge, Shingo Kuroiwa, Fuji Ren and Kenji Kita : 音素依存線形判別分析の検討, 日本音響学会秋季研究発表会, 177-178, Oct. 2001.
218.	財満康通, 安川涼子, Fuji Ren and 相沢輝昭 : 統計手法と言語特徴を用いたテキストアライメント, IEICE Technical Report, Vol.NLC2000, No.75, 1-8, Mar. 2001.
219.	Fuji Ren, Zhou Qiang and Shi Hongchi : Automatic Extraction of Important Sentences and Its Valuation, IEICE Technical Report, Vol.100, No.100, 17-24, May 2000.
220.	Fuji Ren and 財満康通 : 自然言語記述からプログラムへの生成を支援するシステムの提案, 1-12, Mar. 1999.
221.	Fuji Ren, Zhang Jianping and Luo Zhensheng : Word Segment in the Real World, Natural Language Processing, Vol.98, No.2, 79-86, May 1998.
222.	Fuji Ren and 定永靖史 : 統計情報と文章構造特徴に基づく重要文の自動抽出, 情報処理学会研究報告, Vol.98, No.2, 71-78, May 1998.
223.	Fuji Ren and Nie Jianyun : Automatic Word Segmentation of Chinese Texts Based On Sensitive Words Concept, Natural Language Processing, Vol.98, No.1, 17-24, Apr. 1998.
224.	Fuji Ren, 范莉馨, 簡幼良 and 栃内香次 : 対訳コーパスから細粒度翻訳知識の自動獲得手法, 情報処理全大論文集, 247-248, Mar. 1998.
225.	Fuji Ren : Super-Function Based Machine Translation, Natural Language Processing, Vol.97, No.69, 21-28, May 1997.
226.	Fuji Ren : 日中会話文機械翻訳における不適格な表現の処理, 情報処理学会研究報告, Vol.112, No.7, 45-52, 1996.
227.	Fuji Ren : 中日言語のTSPO特徴及びCJMTへの応用について, 人工知能学会全国大会論文集, 637-640, Jun. 1994.
228.	范莉馨, Fuji Ren, 宮永喜一 and 栃内香次 : 中国語表層構造の特徴を利用した中日機械翻訳手法, 情報処理学会第38回全国大会, 129-130, Mar. 1994.
229.	Fuji Ren : 意味属性と表層構造特徴を利用した中国語文の生成, 情報処理学会第38回全国大会, 131-132, Mar. 1994.
230.	Fuji Ren : TSPO特徴を利用した中日機械翻訳, 情報処理学会研究報告, Vol.94, No.77, 129-136, 1994.
231.	Fuji Ren : 21世紀の機械翻訳理想像----超並列機械翻訳, CSK創業記念論文, 1-12, Jun. 1993.
232.	Fuji Ren : 中日機械翻訳における可保留曖昧関係について, 1993年度人工知能学会全国大会論文集, 529-532, Jun. 1993.
233.	Fuji Ren : 超並列機械翻訳システムにおける家族モデルについて, 信学全大, 117, Mar. 1993.
234.	范莉馨, Fuji Ren, 宮永喜一 and 栃内香次 : 機械翻訳における中国語の離合詞について, 信学全大, 118, Mar. 1993.
235.	范莉馨, Fuji Ren, 宮永喜一 and 栃内香次 : 文の分解に基づく中日機械翻訳システム, IEICE Technical Report, Vol.93, No.132, 49-56, 1993.
236.	范莉馨, Fuji Ren, 宮永喜一 and 栃内香次 : 中日機械翻訳における離合詞の処理手法, IEICE Technical Report, Vol.93, No.132, 33-40, 1993.
237.	Fuji Ren : 日中機械翻訳における中国語定語の処理, IEICE Technical Report, Vol.93, No.132, 41-48, 1993.
238.	Fuji Ren : JCMTにおける訳文の特殊な数量表現に関する一考察, 情処研報NLP, Vol.92, No.74, 1-8, Sep. 1992.
239.	Fuji Ren : 超並列機械翻訳のパラダイムについて, 情報処理学会情報科学の会, 1-8, Aug. 1992.
240.	Fuji Ren : 超並列自然言語処理, 情報処理学会情報科学の会, 9-12, Aug. 1992.
241.	Fuji Ren : 分散協調方式を用いた対話文の機械翻訳, 言語処理学会第2回年次大会発表論文集, 5-8, Feb. 1992.
242.	范莉馨, Fuji Ren, 宮永喜一 and 栃内香次 : 構文構造の特徴に着目した中日機械翻訳システム, 電気関係学会北連大論文集, 417-418, Oct. 1991.
243.	范莉馨, Fuji Ren, 宮永喜一 and 栃内香次 : 中日機械翻訳における構文構造の特徴に着目した訳文生成, 信学技報 NLC, Vol.91, No.30, 25-32, Oct. 1991.
244.	范莉馨, Fuji Ren, 宮永喜一 and 栃内香次 : 中国語の複合語生成実験システム, 電気関係学会北連大論文集, 335-336, Oct. 1990.
245.	Fuji Ren, 宮永喜一 and 栃内香次 : 格関係と意味属性による補助語の推定手法, 電気関係学会北連大論文集, 333-334, Oct. 1990.
246.	范莉馨, Fuji Ren, 宮永喜一 and 栃内香次 : 中国語文中の複合語の生成について, 信学技報NLC, Vol.90, No.1, 1-8, May 1990.
247.	Fuji Ren, 范莉馨, 宮永喜一 and 栃内香次 : JCMTSにおける慣用表現の解析手法, 信学技報NLC, Vol.90, No.2, 9-16, May 1990.
248.	范莉馨, Fuji Ren, 宮永喜一 and 栃内香次 : 中国語の浅層解析の実験システムについて, 信学全大論文集D, 91, Mar. 1990.
249.	Fuji Ren, 宮永喜一 and 栃内香次 : 慣用表現の訳文生成について, 92, Mar. 1990.
250.	Fuji Ren, 宮永喜一 and 栃内香次 : 日中機械翻訳システムにおける慣用表現のエンコードとデコード, 信学技報NLC, Vol.89, No.30, 39-46, Oct. 1989.
251.	范莉馨, Fuji Ren, 宮永喜一 and 栃内香次 : 中国語浅層解析の一手法, 電気関係学会北海道市部連合大会論文集, 322-323, Oct. 1989.
252.	Fuji Ren, 宮永喜一 and 栃内香次 : JCMTSにおける慣用表現のエンコードおよびデコード, 338-339, Oct. 1989.
253.	Fuji Ren, 宮永喜一 and 栃内香次 : コード方式日中機械翻訳の実験システムJCMTの概要, 情処研報, Vol.72, No.7, 1-8, May 1989.
254.	Fuji Ren, 宮永喜一 and 栃内香次 : コード方式日中機械翻訳の実験システムについて, 電子情報通信学会全国大会論文集, 6-30, Mar. 1989.
255.	Fuji Ren, 宮永喜一 and 栃内香次 : コード方式日中機械翻訳システムの構想, 332-333, Oct. 1988.
256.	Fuji Ren, 宮永喜一 and 栃内香次 : グラフ故障シミュレーションアルゴリズムに関する研究, IEICE Technical Report, Vol.88-63, 1-8, Oct. 1988.

Et cetera, Workshop:

1.	Changqin Quan and Fuji Ren : Chinese Emotional Expressions Analysis: Construction of a Blog Emotion Corpus, 情報処理学会研究報告, Vol.2009, No.NL-189, 49-55, Jan. 2009.
2.	Li Yun, Huang Kaiyan, Seiji Tsuchiya and Fuji Ren : Searching and Computing for Vocabularies with Semantic Correlations from Chinese Wikipedia, 情報処理学会研究報告, Vol.2008, No.NL-184, 105-112, Mar. 2008. (Summary) This paper introduces our research and experiment on searching for semantically correlated vocabularies in Chinese Wikipedia pages and computing semantic correlations. Based on the 54, 745 structured documents generated from Wikipedia pages, we explore about 400,000 pairs of Wikipedia vocabularies considering of hyperlinks, overlapped text and document positions. Semantic relatedness is calculated based on the relatedness of Wikipedia documents. From comparing experiment we analyze the reliability of our measures and some other properties.
3.	劉曄, 籐智, Seiji Tsuchiya and Fuji Ren : A Study of the Guidebook System with Application in SVM and Syntactic Analysis based on VSM, 情報処理学会研究報告, Vol.2008, No.NL-184, 19-24, Mar. 2008. (Summary) Numerous various kinds of information on present Web, make the retrieval possible to everything exist. However, excessive information also make it difficult to retrieve the one you really want, particularly, when the knowledge is scarce(for instance, it goes sightseeing). Therefore, in our research, we propose a sightseeing guide system which classify the user's query with SVM and then calculate the similarity by VSM. In the experiment result, the accuracy was 55% and about 22% higher than the one without VSM classification. It can be said that the proposed system is effective.
4.	足立征士, Seiji Tsuchiya and Fuji Ren : 単語表記と音声特徴を用いた聞き手の感情推定手法の提案, 人工知能学会言語・音声理解と対話処理研究会, Vol.SIG-SLUD, 9-14, Mar. 2008.
5.	袴田愛, Seiji Tsuchiya and Fuji Ren : 心的モデルを用いた会話エージェントの表情生成手法, 人工知能学会言語・音声理解と対話処理研究会, Vol.SIG-SLUD, 3-8, Mar. 2008.
6.	四宮瑞穂, 三品賢一, Seiji Tsuchiya and Fuji Ren : Consideration about the Effectiveness of the Emotion Dictionary for Extracting Opinions from News Articles, IEICE Technical Report, Vol.TL2007, No.46, 31-36, 2007. (Summary) Opinions are included a lot of news articles such as editorial articles. This kind of information is important for us. We pay attention to the emotion expressions which could be used to express opinins. Then we do a investigation on the effectiveness of opinion extraction from news articles using emotion words. The articles employed are editorial articles from plural news companies and news on the result of professional baseball games. Opinions are limited among "positive" and "negative" and "neutral". We compared the precision of opinion extraction between the result using emotion word dictionary and the result using a word dictionary which based on counting the frequency of positive and negative words. On the news of professional baseball games the emotional dictionary method got a precision of 71%, but on the editorial articles, the result is only 36%. Which is weaker than the result of the frequencymethod. We also studied the effective part of speech for opinion extraction from news articles.
7.	久積克年, Ryosuke Sumitomo, Seiji Tsuchiya and Fuji Ren : Extraction of the term having the explicit relation, IEICE Technical Report, Vol.TL2007, No.46, 31-36, 2007. (Summary) This paper present an extraction method based on terms have the explicit relations. Usually, it is difficule to extract explicit term relations. However, explicit relations can help us in knowledge information systems and text-mining. Therefore, we propose a method that using the following assumption. It relates to the term that appears at the same time in the same sentence. It is a relation corresponding to the term in the sentence including the same term. The proposed technique uses co-occurrence frequency and number of retrieval pages. We did an evaluation experiment. The purposed experiment extract "X" that becomes the relation of "fire-case-X". The effectiveness of the proposed method was verified by the experiment.
8.	Junko Minato, Matsumoto Kazuyuki, Seiji Tsuchiya, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : A Study on Color and Emotion in Japanese and English, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 363, Sep. 2007.
9.	Zhi Teng, Ye Liu, Fuji Ren and Shingo Kuroiwa : Search Computing Based on Google API for QA System, 情報処理学会研究報告, Vol.2007, No.76, 91-99, Jul. 2007. (Summary) Search computing has been widely used in the field of natural language processing. In recent years, the QA System has been successfully applied to a number of applications, but the limited amounts and the incertitude of answer weremuch in evidence. The wealth of information on the web makes it an attractive and simple resource for seeking quick information. Recently being quite successful in providing keyword based access to web pages, commercial search portals still lack the ability to answer questions expressed in a natural language of Chinese. In this paper we propose a new method based on the Google WEB API for the QA System in restricted domains. The experiment showed that this method can get the more accurate result.
10.	篠山学, Seiji Tsuchiya, Shingo Kuroiwa and Fuji Ren : Extracting Date/Time Expressions in Super-Function based Japanese-English Machine Translation, 情報処理学会研究報告, Vol.2007, No.76, 163-168, Jul. 2007. (Summary) Super-Function Based Machine Translation(SFBMT) which is a type of Example-Based Machine Translation has a feature which makes it possible to expand the coverage of examples by changing nouns into variables, however, there were problems extracting entire date/time expressions containing parts-of-speech other than nouns, because only nouns/numbers were changed into variables. We describe a method for extracting date/time expressions for SFBMT. SFBMT uses noun determination rules to extract nouns and a bilingual dictionary to obtain correspondence of the extracted nouns between the source and the target languages. In this method, we add a rule to extract date/time expressions and then extract date/time expressions from a Japanese-English bilingual corpus. The evaluation results shows that the precision of this method for Japanese sentences is 96.7%, with a recall of 98.2% and the precision for English sentences is 94.7%, with a recall of 92.7%.
11.	藤原祥平, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : 分散音声認識を用いた音声対話システムの検討, 言語・音声理解と対話処理研究会, Vol.2007, No.A701, 13-18, Jul. 2007.
12.	喜多雅彦, Satoru Tsuge, Shingo Kuroiwa and Fuji Ren : 多数の話者モデル内での順位情報を用いた話者照合, 言語・音声理解と対話処理研究会, Vol.2007, No.A701, 7-12, Jul. 2007.
13.	平井孝則, Ryosuke Sumitomo, Shingo Kuroiwa and Fuji Ren : 突発性雑音に頑健な音声認識実現のための繰り返し発声を用いた音声強調法の提案, 言語・音声理解と対話処理研究会, Vol.2007, No.701, 1-6, Jul. 2007.
14.	三品賢一, Seiji Tsuchiya, Shingo Kuroiwa and Fuji Ren : N-gram出現頻度を用いた感情類似度計算, 情報処理学会研究報告, Vol.2007, No.76, 37-42, Jul. 2007.
15.	山本麻由, Seiji Tsuchiya, Shingo Kuroiwa and Fuji Ren : Emotion Classification for Emotion Corpus Construction, 情報処理学会研究報告, Vol.2007, No.76, 25-30, Jul. 2007. (Summary) In this paper, we aim to develop Emotion corpus automatically using Naive Bayes Classifier. Emotion corpus is language data with emotion tags. Language data is the corpus which made by the sentences that we collected from web. Emotion tag stands for emotion of the people who wrote the sentences at the time. At first, we put emotion tags on the language data we collected. Next,we classify the language data using the Naive Bayes Classifier based on this data set, and I confirm the effectiveness of the method.
16.	川島宏文, Seiji Tsuchiya, Shingo Kuroiwa and Fuji Ren : Construction of interactive guide contents in practical conversation system, 情報処理学会研究報告, Vol.2007, No.76, 1-6, Jul. 2007. (Summary) Current sightseeing guide contents on web provide information in one direction. We made an interactive guide contents to answer user's question by using a CAIWA system. The contents show tourist spots in Tokushima by introducing their feature or historical background with video pictures. Users can ask questions by inputting text or speech anytime during a video and can obtain answers by video pictures and audio commentary. As a result, we achieved flexible question and answer communication between the users and the system.
17.	Junko Minato, Bracewell B. David, Shingo Kuroiwa and Fuji Ren : Automatically Identifying Emotion from Bilingual Text, 2005 Shikoku-section Joint Convention Record of The Institutes of Electrical and Related Engineers, 351, Sep. 2005. (Summary) Emotion is important for understanding the semantics of language. As such, much research has been done in finding the emotion from a user or from a text. For example, research has been done in linking facial expressions to affective meaning [1]. Also, in [2] they look at tagging words with their emotion. In this paper, we will look at finding emotion from bilingual texts. The target languages are Japanese and English. The first step is to build an emotion ontology, which will be used by the system to determine the emotion of a word. Then we will build a system to find emotion words and their corresponding emotions in bilingual texts. (Keyword) Affective computing / Corpus / Ontology
18.	Shingo Kuroiwa, Satoru Tsuge, Fuji Ren and Seishi Kitayama : 統計的手法を用いた音声信号の復元手法の改良, Bulletin of Faculty of Engineering, The University of Tokushima, Vol.50, 26-32, Mar. 2005. (Tokushima University Institutional Repository) ● Metadata: 45182 (Tokushima University Institutional Repository: 45182)
19.	Yoshiyuki Umeda, Ippei Fukuda, Satoru Tsuge, Fuji Ren and Shingo Kuroiwa : Distributed Speaker Recognition using Earth Mover's Distance, IEICE Technical Report, Vol.SP2004, No.51, 25-30, Aug. 2004. (Summary) 本稿ではノンパラメトリックな話者認識手法を提案する．話者モデルと認識対象データはそれぞれ，話者登録用音声並びに認識対象音声から得られた特徴パラメータを量子化したデータの集合 (ノンパラメトリックな分布) で構成される．話者認識時に必要となる距離尺度には， Earth Mover's Distance を用いる．提案手法の有効性を検証するため，特徴パラメータ抽出に ETSI 標準 DSR フロントエンドを用いて，男性話者21名によるテキスト独立型話者識別実験を行い良好な結果を得た．
20.	Yoji Mori, Satoru Tsuge, Fuji Ren and Shingo Kuroiwa : Wind Noise Reduction Method Using Multiple Noise Models, IEICE Technical Report, Vol.SP2004, No.52, 31-36, Aug. 2004.
21.	森陽司, Satoru Tsuge, Fuji Ren and Shingo Kuroiwa : 複数の雑音モデルを用いた風雑音除去手法, IEICE Technical Report, Vol.SP2004-52, 31-36, Aug. 2004.
22.	Yusuke Konishi, Tadashi Shoda, Fuji Ren and Shingo Kuroiwa : 自然言語処理技術を用いた中学理科教授学習システムの研究, IEICE Technical Report, Vol.NLC2003-11, 61-66, Jun. 2003.
23.	長野信男, Fuji Ren and Shingo Kuroiwa : 顔特徴を用いた表情の認識, IEICE Technical Report, Vol.NLC2003-11, 61-66, Jun. 2003.

Report:

1.	Shingo Kuroiwa, Kenji Kita, Fuji Ren and Satoru Tsuge : 分散型話者照合方式に関する研究, 平成14年度∼平成16年度科学研究費補助金(基盤研究(B)(2))研究成果報告書, Vol.14350204, 1-227, May 2005.

Patent:

1.	Fuji Ren : 「スーパー関数，機械翻訳方式」, 2004-246349, .
2.	Fuji Ren and Rishin Han : 「離合詞処理方式」, 5-226640, .
3.	Fuji Ren and Rishin Han : 「中日機械翻訳方式，関連語」, 5-226639, .
4.	Fuji Ren : 「日中機械翻訳における定語処理方式」, 5-197949, .
5.	Fuji Ren and Rishin Han : 「中国語複合語自動合成装置」, 5-115233, .
6.	Fuji Ren : 「日中機械翻訳方式」補助語, 5-81346, .
7.	Fuji Ren : 「日中機械翻訳方式」常用文型, 5-81345, .

Grants-in-Aid for Scientific Research (KAKEN Grants Database @ NII.ac.jp)

異なるコミュニティにおいて誤解されやすい表現の感性的言語変換に関する研究 (Project/Area Number: 20K12027 )
Dialogue continuation by utterance induction using multi-attribute sensitivity empathy (Project/Area Number: 15H02770 )
Creation of an evolutionary advanced intelligent robot (Project/Area Number: 15H01712 )
To Create Robot Mind and Apply it to Nursing Robots (Project/Area Number: 22240021 )
Establishment of an academic system of Enriching Mental Engineering (Project/Area Number: 21650030 )
Psychiatric Outcome Management System Using Clinical Pathways : Development, Evaluation, and Improvement (Project/Area Number: 20390544 )
Creation of ubiquitous learning environments based on intelligence media technology (Project/Area Number: 19300029 )
統計的手法を用いた知識情報モデルに基づく知的信号処理手法に関する研究 (Project/Area Number: 17656128 )
Analysis of Intra-Speaker Variation and Development of Distributed Speaker Recognition System (Project/Area Number: 17300065 )
Development of the "Objective Emotion Display System" for Educating Therapeutic Communication Skills (Project/Area Number: 15390680 )
Machine-Aided Writing System based on Super-Function and Intellectual Corpus (Project/Area Number: 14380166 )
A Study of Distributed Speaker Recognition Methods (Project/Area Number: 14350204 )
自然言語処理技術を用いた理科教授学習システムに関する研究 (Project/Area Number: 14022237 )
Study on Constraint Query Processing for Heterogeneous Tree Databases (Project/Area Number: 12680394 )
Super-Function Based Japanese-Chinese-English Machine Translation and Information Retrieval (Project/Area Number: 11480080 )
JCE-TC Japanese-Chinese-English Translation Corpus and Its Application (Project/Area Number: 09044179 )
T+文法の開発及びその日中言語処理への応用に関する研究 (Project/Area Number: 08878050 )
生物科学分野の分類情報を統合した大量知識ベースの構築・利用技術に関する研究開発 (Project/Area Number: 08283104 )
協調・融合技術を用いる中日機械翻訳システムに関する研究 (Project/Area Number: 07780344 )
Search by Researcher Number (20264947)

Professor Emeritus : Ren, Fuji

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Grants-in-Aid for Scientific Research (KAKEN Grants Database @ NII.ac.jp)