Insights into the genomic evolution of insects from cricket genomes.

Most of our knowledge of insect genomes comes from Holometabolous species, which undergo complete metamorphosis and have genomes typically under 2 Gb with little signs of DNA methylation. In contrast, Hemimetabolous insects undergo the presumed ancestral process of incomplete metamorphosis, and have larger genomes with high levels of DNA methylation. Hemimetabolous species from the Orthopteran order (grasshoppers and crickets) have some of the largest known insect genomes. What drives the evolution of these unusual insect genome sizes, remains unknown. Here we report the sequencing, assembly and annotation of the 1.66-Gb genome of the Mediterranean field cricket Gryllus bimaculatus, and the annotation of the 1.60-Gb genome of the Hawaiian cricket Laupala kohalensis. We compare these two cricket genomes with those of 14 additional insects and find evidence that hemimetabolous genomes expanded due to transposable element activity. Based on the ratio of observed to expected CpG sites, we find higher conservation and stronger purifying selection of methylated genes than non-methylated genes. Finally, our analysis suggests an expansion of the pickpocket class V gene family in crickets, which we speculate might play a role in the evolution of cricket courtship, including their characteristic chirping.


Efficient String Dictionary Compression Using String Dictionaries

文字列辞書を用いた効率的な文字列圧縮の検討と評価

日本データベース学会和文論文誌

日本データベース学会和文論文誌


Compressed double-array tries for string dictionaries supporting fast lookup


A compression method of double-array structures using linear functions


A construction method by divided double array structures

International Journal of Intelligent Systems Technologies and Applications


A new compression method for double-array structures by a hierarchical representation


Improved dialogue communication systems for individuals with dementia

International Journal of Computer Applications in Technology


Double array structures based on byte segmentation for n-gram


Compression of double array structures for fixed length keywords

A trie is one of the data structures for keyword matching. The double array representation combines retrieval speed of the matrix form with compactness of the list form. LOUDS is a succinct data structure using bit-string. Retrieval speed of LOUDS is not faster than that of the double array, but its space usage is smaller. This paper proposes a compressed version of the double array by dividing the trie into multiple levels and removing the BASE array from the double array. According to the presented experimental results the retrieval speed of the presented method is almost the same as the double array, and its space usage is compressed to 66% comparing with LOUDS.

トライはキーワードマッチングのデータ構造である．トライの実装法であるダブル配列はマトリックス表現のスピードとリスト表現のコンパクト性を併せ持つデータ構造である．LOUDSはダブル配列よりも検索は速くないが，メモリサイズは小さい．本論文では，ダブル配列からBASEを削除し，トライを分割することにより圧縮する手法を提案する．実験より検索速度はダブル配列と同様で，LOUDSより66%のサイズとなった．


Agent based communication systems for elders using a reminiscence therapy

A dialogue communication between persons is efficient for dementia care for elderly people. Also, a reminiscence therapy is to activate brains by telling his/her experience and past life memories. Therefore, this paper proposes agent-based communication system using questions about personal histories as topics of dialogue communications. We examine how dialogues of dementia patients are induced or continued by questions and answers by personal history, and which topics are effective for dementia patients. From experimental results, it turns out that especially "Place of birth", "Old song" and "Favorite food" are interested questions for the elders. Moreover, "Question Topic" is more efficient than "Question difficulty level" for dialogue supports.

人間同士の対話は高齢者の認知症治療に効果がある．回想法は，過去の経験や人生の思い出を話すことにより脳を活性化し，認知症の治療に効果がある．この論文では，対話の話題として個人の歴史を質問するエージェントベースのコミュニケーションシステムを提案する．実験により，「出生地」「昔の歌」「好きな食べ物」が高齢者を興味を持つことがわかった．さらに質問の話題は，質問の難しさより効果があることもわかった．


A method of extraction and visualisation for relationships among objects on web

This paper aims to extract object relationships including the direction of the relation considering context information. In the proposal method, related words that are objects related to the object given as an input word are acquired at first. And object relationships between an input word and each related word are extracted. Moreover, the system that visualises related words and the object relationships as a correlation diagram is implemented. From the experiment for extraction of object relationships, the accuracy of the correct answer rate of 80% or more, was obtained by using the proposal method.

本論文は文脈情報を考慮してオブジェクト間の関係をその向きとともに抽出する．提案手法では，最初にあるオブジェクトに関係するオブジェクトである関係語を入力として与える．そして，入力語と関連する各関係語が抽出される．さらに，関係語とオブジェクト間の関係を相関図として可視化するシステムを実装する．提案手法を用いたオブジェクト関係抽出実験により，80%以上の正解率が得られた．


The Determination of Affirmative and Negative Intentions for Indirect Speech Acts by a Recommendation Tree

This paper defines a recommendation tree and proposes an algorithm of deriving intentions of indirect speech acts by the tree. In the proposed method, a recommendation condition (RC) is introduced and it is classified into a required RC, a selectable RC, and a not-selectable RC. The recommendation tree is constructed by nodes and edges corresponding to these three conditions. The deriving algorithm determines affirmative and negative intentions of indirect speech acts by tracing the trees. From experimental results, it is verified that the accuracy of the proposed method is about 40 points higher than the traditional method.

本論文では，推薦木を定義し，推薦木から間接発話の意図導出アルゴリズムを提案する．提案手法では，3つの推薦状態(必要状態，選択可能状態，選択不可能状態)に分類する．推薦木はこれらの3つの状態に対応するノードとエッジによって構築される．意図導出アルゴリズムは木をたどることによって間接発話の肯定否定を判定する．実験結果から，提案手法は従来法に比べて約40ポイントの精度向上が確認された．

International Journal of Advanced Computer Science and Applications


An incremental construction method of a large-scale thesaurus using co-occurrence information

This paper aims to construct a hierarchical large-scale thesaurus by a clustering scheme based on co-occurrence information among words. In the proposed clustering algorithm, the Kullback-Leibler divergence is introduced as a similarity measurement in order to judge superordinate and subordinate relations. Besides, the thesaurus tree can be incrementally updated in each node for a minute change such as the addition of unknown words. In order to evaluate the presented method, a thesaurus consisting of about 60,000 words is made by using about 16 million co-occurrence relationships extracted from the Google N-gram.

本論文は，単語間の共起情報を基にしたクラスタリング手法を用いて階層的な大規模シソーラスを構築することを目的にしている．提案するクラスタリングアルゴリズムでは，上位下位関係を判定するための類似度として，カルバックライブラー距離を用いている．さらに，未知語の追加のような小さな変更に対応するためシソーラスを増加的に更新できるようになっている．評価実験で，Google N-gram から取り出した共起情報約1600万関係から，約6万語から成るシソーラスを構築した．


Effectiveness of an implementation method for retrieving similar strings by trie structures

Demands for retrieving similar strings have been increasing. There are many methods for retrieving similar strings, and most methods must build dedicated dictionaries. In Ubiquitous Environments, because the storage capacity is often limited, the dictionary size must be compact. Therefore, this paper proposes a data structure and a fast retrieval algorithm for similar strings by existing tries. Moreover the retrieval speed for some implementation methods of a trie is compared. From experimental results, the retrieval speed of the proposed method is 2.6-3.5 times faster than that of the conventional method. The retrieval speed of list structures as an implementation method is the fastest.

類似文字列の検索要求は高まっている．類似検索の手法は幾つかあり，多くの手法は専用の辞書を構築しなければならない．ユビキタス環境では容量に制限があり，辞書はコンパクトでなければならない．本論文では，既に存在するトライを用いて類似文字列検索を高速に行う手法を提案する．さらに他の手法との比較を行う．実験より，提案法は2.6∼3.5倍高速になり，リスト構造で構築するのが最も早かった．


An Efficient Method of Summarizing Documents Using Impression Measurements

Generally, novels are typical documents providing sentimental impression for readers. However, newspapers deliver different impressions for new knowledge because they inform readers about current events, informative articles and diverse features. The proposed method introduces impressive expressions for newspapers and their measurements are applied to the NMF method. From 100 KB text data of experimental results by the proposed method, it turns out that the matrix size reduces by 80 % and the computation of the NMF method becomes 7 times faster than with the original method, without degrading the relevancy of extracted sentences.

一般に，小説は読者に感情的な印象を与える文書の典型である．しかし，新聞は，読者に時事や有益な情報を提供するため，新知見への異なった印象を与える．提案手法は，新聞記事での印象的表現を導入し，NMF法を適用して判定する．100 KBテキストでの実験で，行列サイズを80%縮小し，NMF法の処理時間が精度低下なく7倍高速になることがわかった．


Document summarisation on mobile devices using non-negative matrix factorisation

This paper proposes compact and fast approaches that can summarise documents on mobile devices efficiently. The proposed method improves unsupervised schemes using the original non-negative matrix factorisation (NMF) that can determine the paragraph precedence without morphological and syntax analyses. In order to speed up the summarisation, the proposed technique is applied to the NMF method. From simulation results for test data of DUC2006, it turns out that the matrix size could be reduced by about 95% and the precision of summarisation speeding becomes 8.5 times faster than the original method without degrading the precision of extracted paragraphs.

本論文は，モバイル機器において効率的に文書要約できるコンパクトかつ高速な手法を提案する．提案手法は，形態素，構文解析なしに段落の順位を決定するオリジナルの非負値行列因子分解(NMF)を利用して教師なし手法を改善する．要約の高速化のため，提案手法はNMFを適用する．シミュレーションの結果，オリジナル手法に対して，文抽出精度を落とすことなく，行列のサイズを95%減少でき，要約速度が約8.5倍高速になった．

International Journal of Computer Applications in Technology


A Method of Combination of Language Understanding with Touch-Based Communication Robots

Studies of robots which aim to entertain and to be conversational partners of the live-alone become very important. The robots are classified into DBC (Dialogue-Based Communication) robots and TBC (Touch-Based Communication) robots. This paper proposes a response algorithm that can combine conversational information and touch information from humans. From the experiment for impressions of robot responses with 11 subjects, it turns out that the proposed method with combination of DBC and TBC is improved compared to only TBC or DBC.

会話のパートナーとしてロボットを利用する研究が重要となっている．ロボットは，DBC (Dialogue-Based Communication)ロボットと，TBC (Touch-Based Communication)ロボットに分けられる．本研究では人間との会話と接触による情報を用いたアルゴリズムの提案を行った．実験を行った結果，TBCやDBCを単独で用いた時より，有効な結果が得られた．

International Journal of Intelligence Science


A Context Analysis Scheme of Detecting Personal and Confidential Information

In order to support the supervision of personal and confidential (PC) information, there are many detection systems depending on PC texts. This paper presents a new detection scheme for non-PC texts by using context analysis. The heart of the new approach is introducing neglect (NEG) expressions that can cancel the detected PC information. It enables us to reduce extra-detections or human efforts for non-PC texts. Experimental results for context data show that the improvement of the presented method becomes 66.5% compared with the traditional methods. Moreover, the human efforts reduce by about 80% comparing to by using the traditional methods.

個人・守秘情報の監視をサポートするために，個人・守秘文書に依存した多くの検出システムが存在する．本論文は，文脈処理を用いた非個人・守秘テキストに対する新しい検出法を提案する．提案手法では，検出された個人・守秘情報を取り消すための無視表現が導入されている．非個人・守秘テキストに対する過検出や人の労力を軽減することを可能にする．文脈データに対する実験結果で，提案法は従来法に対して66.5%の改善が得られた．また，従来法の利用に比べて人の労力が80%軽減された．

International Journal of Innovative Computing, Information and Control


A new approach for Arabic text classification using Arabic field-association terms

Field-association (FA) terms give us the knowledge to identify document fields using a limited set of discriminating terms. However, previous studies are based on FA terms in English and Japanese, and the extension of FA terms to other languages such as Arabic could benefit future research in the field. This paper proposes amended text classification methodology based on field association terms in Arabic language. Presented approach is compared with Naive Bayes (NB) and kNN classifiers on 5,959 documents from Wikipedia dumps and Alhayah news. The new approach achieved a precision of 80.65% followed by NB (72.79%) and kNN (36.15%).

分野連想語は限定された識別語の集合を用いて，文書分野を特定する知識を与える．しかし，分野連想語の従来研究は英語や日本語に基づくため，アラビア語などの他の言語への拡張は今後の研究の余地がある．本論文は，アラビア語の文や連想語に基づいた文書分類手法の拡張を提案する．提案手法はWikipediaとAlhayahニュースの5,959文書に対して比較実験を行い，ナイーブベイズ72.79%とkNN法36.15%に対し，80.65%の精度を達成した．

Journal of the American Society for Information Science and Technology


A fast search method of similar strings from dictionaries

Demands for retrieving similar strings to an input string from dictionaries have been increasing. The edit distance is necessary to retrieve information from a large amount of data using the similarity between two strings. However, drawback of this method is time consumption because the input string must be compared with all strings in dictionaries. This study proposes a new technique for retrieving similar strings from dictionaries at high speed. The method presented can retrieve all similar strings 14 times faster than unigram methods although the edit distance is 3.

入力文字列に類似した文字列の検索要求が高まっている．2つの文字列の類似度として編集距離が用いられる．しかしながら，この方法は辞書のすべての単語と編集距離の計算をしなければならないので，非常に遅い．本論文では，辞書から高速に類似文字列を検索する新しい手法を提案する．提案手法は編集距離3のすべて文字列を従来法より14倍高速に検索できた．


Context Constraint Disambiguation of Word Semantics by Field Association Schemes

This paper presents a new scheme for solving context ambiguities using a field association scheme. In this paper, a formal disambiguation algorithm is proposed to control the scope for a set of variable number of sentences with ambiguities as well as solve ambiguities by calculating the weight of fields. In the experiments, 52 English and 20 Chinese words are disambiguated by using 104,532 Chinese and 38,372 English field association terms. The accuracy of the proposed field association scheme for context ambiguities is 65% higher than the case frame method.

本論文は，分野連想体系を用いて文脈の曖昧性を解消する新しい手法を提案する．本論文では，分野重みの計算によって曖昧性を解消するとともに，曖昧性を持つ複数の文を1セットにした範囲を制御することで，形式的に曖昧解消するアルゴリズムを提案する．実験では，英単語52語と中国単語20語が，中国語104,532語と英語38,372語の分野連想語を用いることで曖昧性が解消された． 文脈の曖昧性に対する分野連想体系を用いた提案法の精度は格フレーム手法より65%高かった．


A method of extracting malicious expressions in bulletin board systems by using context analysis

Malicious postings to bulletin board systems about crimes are serious problems for serving companies and users. This paper presents a new filtering algorithm that can recover the error rate of false positive for non-malicious articles by using context analysis. The presented scheme builds detecting knowledge by introducing multi-attribute rules. By the experimental results for 11,019 test data, it turns out that sensitivity and specificity of the presented method become 38.7 and 24.1 points higher than traditional method, respectively.

電子掲示板への犯罪に関する有害な投稿は，会社やユーザに役立てる上での深刻な問題である．本論文は，文脈処理を用いて，非有害記事に対する誤判定の誤り率を回復できる新しいフィルタリングアルゴリズムを提案する．提案法は多属性ルールを導入することによって検出知識を構築する．11,019のテストデータによる実験結果で，提案手法の感度と特異度が従来手法よりそれぞれ38.7ポイントと24.1ポイント向上することがわかった．


Extraction, selection and ranking of Field Association (FA) Terms from domain-specific corpora for building a comprehensive FA terms dictionary

Field Association (FA) Terms words or phrases that serve to identify document fields are effective in document classification and similar file retrieval. But the problem lies in the lack of an effective method to extract and select relevant FA Terms to build a comprehensive dictionary of FA Terms. This paper presents a new method to extract, select and rank FA Terms from domain-specific corpora. Experimental evaluation on 21 fields selected up to 2,517 FA Terms at precision and recall of 74-97and 65-98. This is better than the traditional methods.

分野連想語は文書の分野を識別することができ，文書分類や類似文書検索に有効である．しかし，分野連想語を網羅的に抽出し，選別する手法が存在しない．本論文では，ドメイン固有の文書から分野連想語を抽出・選別し，ランク付けする手法を提案する．21分野を用いた実験から，平均2,517の分野連想後を抽出し，適合率74∼97%，再現率65∼98%となった．これは従来法より優れた結果である．


New methods for compression of MP double array by compact management of suffixes

Minimal Prefix (MP) double array is an efficient data structure for a trie. However, its space efficiency is degraded by the non-compact management of suffixes. This paper presents three methods to compress the MP double array. The first two methods compress the MP double array by accommodating short suffixes inside the leaf nodes, and pruning leaf nodes corresponding to the end marker symbol. The third method eliminates empty spaces in the array that holds suffixes. Compared to a Ternary Search Tree, the key retrieval of the compressed MP double array is 50% faster and its size is 3-5 times smaller.

MPダブル配列はトライを実現する効率的なデータ構造である．しかしながら，接尾辞をコンパクトにせずに実装している．本論文ではMPダブル配列を圧縮する3つの手法を提案している．最初の2手法は，終端記号に対応している葉ノードを枝刈りすることにより圧縮し，3つ目の手法は接尾辞を格納している配列の空き要素の予測を行う．従来法のTSTと比較することにより，50倍高速になり，記憶容量は3∼5倍小さくなった．


Relevant estimation among fields using field association words

In recent years, there has been a tremendous growth of online text information related to the explosive growth of the web. Humans can recognise subjects of document fields by reading only some relevant specific words called field association words in the field. This paper presents a method of relevant estimation among fields by using field association words. Two methods are proposed in this paper: first is a method of extraction of co-occurrence among fields and the second is a method of judgment of similarity among fields as the methods of relevant estimation among fields. From experimental results, precision of the first method is high when relevance among fields is very high and considering direction of fields, preferable results are obtained in the second method.

近年，webの急速な発展により，非常に有益な情報を取得できるようになった．人間は数単語を読むだけで文書の分野を認識することができる．この単語は分野連想語と呼ばれる．本研究では，分野連想語を用いて，指定された分野に共起する分野と，類似する分野を抽出する手法を提案する．実験により，関連性と方向性を高精度で判定できることを確認した．

International Journal of Computer Applications in Technology


An automatic extraction method of word tendency judgement for specific subjects

This paper focuses on word tendencies in documents and presents an automatic extraction method for specific subject. Field judgment is conducted by using field association words and similarity among word tendencies, and other word tendencies are computed with information. Then word tendencies which have the same subject are grouped as one group and the important word tendencies are chosen from that group. Finally, a system suggests word tendencies from specific subjects and fields are implemented. From the experimental result, about 67% of suggested word tendencies have been associated with popular subjects.

本論文は，文書内の話題語に焦点を当て，特定の話題を自動抽出する手法を提案する．分野連想語を用いた分野判定と，話題語間の類似度計算が行われる．そして，同様の話題を持つ話題語をグループ化し，グループ内の重要語を決定する．最終的に話題語と特定の話題，分野を提示するシステムを構築した．実験結果から，およそ67%の提示された話題語がポピュラーな話題を示していることがわかった．


A method to implement effective My-page service system using three-dimensional vectors


An Implementations Method for Word Tendency Using Decision Tree


A compressed trie structure using divided keys

We present a data structure to retrieve compound words efficiently. Compound words are created by combining in infinitum. Purpose of this research is to improve the space efficiency by dividing keys based on double array structure.

本研究では，複合語を効率的に記憶・検索可能なデータ構造を提案する．複合語は単語の組み合わせで無限に造語されるため，単語辞書の記憶容量の多くを占有するという問題があった．本研究では，ダブル配列構造を基礎とし，キーを分割して格納することによって，記憶量を削減することを目的とする．


A method for extracting knowledge from medical texts including numerical representation

Numeric information is very important to understand numbers in texts of medical opinions. This paper presents a method for determining not only numbers but also expressions of modification to expand the range of corresponding numbers. The meaning of sentences is often determined by the combination of number expressions and their object words. Therefore, the presented method categories with each meaning of expressions of modification and range expressions. According to experimental results for 948 Computer Tomography (CT) findings, the precision and recall for the extraction of number expressions are 98.23% and 97.62%, respectively. Moreover, the accuracy for the extraction of object words is 90.22%.

医療文書において数値表現は非常に重要である．本論文では，数字だけでなく数字を用いた範囲について修飾表現も抽出する手法を提案する．文の意味はたびたび数値表現と周囲の単語において決定される．従って，提案手法では修飾表現と範囲表現の意味をカテゴリー分けする．948のCT所見文を用いた実験により，数値表現の抽出の適合率と再現率はそれぞれ98.23%と97.62%となった．さらに，目的語の抽出率は90.22%だった．


Accuracy improvement for a voice recognition using field association knowledge


Estimation of FAQ knowledge bases by using semantic expressions for questions and answers

This paper presents an estimation method of the FAQ service by introducing the following measurements: 1) user's disrepute for products which defined by four types of classifying questions (IMPOSSIBLE, SIDE EFFECT, INSUFFICIENT and UNCLEAR) and the degree for each type is defined. 2) kindness for solutions replied which defined by four types of classifying answers (ACTION, CONFIRMATION, EXPLANATION, and NO PROBLEM) and the degree for each type is defined. 3) comprehension for answers which defined by semantic expressions of questions and answers. 4) sufficiency and quality for the whole FAQ service that introduced by the measurements 1, 2 and 3.

本論文は次の尺度によってFAQサービスを評価する手法を提案する．1) ユーザーの製品に対する不満を，質問分類によって4つの苦情レベルに分ける．2) 質問に対する回答を4つの親切レベルに分類する．3) 質問，回答の感性表現を用いて回答の理解レベルを定義する．4) 苦情レベル，親切レベル，理解レベルを用いてFAQサービス全体の質と満足度を示す．


Ranking of field association terms using Co-word analysis

Information retrieval involves finding some desired information in a store of information or a database. In this paper, Co-word analysis will be used to achieve a ranking of a selected sample of FA terms. Based on this ranking a better arranging of search results can be achieved. Experimental results achieved using 41 MB of data. This corpus was chosen to be distributed over 11 sub-fields of the field sports from the experimental results, the average precision increased by 18.3%, and the average precision increased by 17.2% after applying the proposed arranging scheme depending on a formula based on ``TF∗IDF'' to count the terms weights.

情報検索では，情報やデータベースから希望する情報の検索が行われている本論文では，選択された分野連想語のランキングを得るために，共通語を使用する．このランキングを用いることにより，よりよい結果を取得することが可能となる．41MBのコーパスを用いた実験よりは，スポーツ分野の11以上のサブ分野を抽出することができた．平均適合率は18.3%向上し，平均再現率は，17.2%向上し，提案手法の有効性を実証した．


Improvement of building field association term dictionary using passage retrieval

This paper proposes a new approach for extracting FA terms using passage (portions of a document text) technique rather than extracting them from the whole documents. This approach extracts FA terms more accurately than the earlier approach. According to experimental results, it turns out that by using the new approach about 24% more relevant FA terms are appending to the earlier FA term dictionary and around 32% irrelevant FA terms are deleted. Moreover, precision and recall are achieved 98% and 94% respectively using the new approach.

本論文は，文書全体からの抽出ではなく，節を用いることで分野連想語を抽出する新しい手法を提案する．本手法は従来手法より正確に分野連想語を抽出する．実験結果より，提案手法は約24%のより関連する分野連想語を登録でき，従来手法の分野連想語辞書から約32%の無関係な語を削除したことがわかった．また，提案手法を用いた精度と再現率はそれぞれ98%と94%を達成した．


Disambiguation of Field Association Terms using Co-occurrence Information

Human can recognize the subject of document fields by reading only some relevant specific word called Field Association terms. Various researches focused on how to extract FA terms depending on levels or frequency information. Therefore, the extracted FA terms are connected to several different fields. The traditional method causes misleading irrelevant terms to be registered because the quality of the resulting FA terms depends on levels and frequency information only. This paper proposes a new technique to disambiguate FA terms using co-occurrence information. From the experimental results, Recall and Precision are about 17% similar to 20% higher than the traditional methods.

人間は，分野連想語と呼ばれる分野に関連する語を読むだけでその文章の分野を判定できる．これまでの研究は，レベルや頻度を用いて分野連想語を抽出しているので，分野連想語は，複数の異なる分野に対応付けられている．従来法では分野連想語の質は，レベルや頻度のみに依存しているので，重要でない語が抽出される場合がある．本論文では，共起を用いた分野連想語の抽出法を提案する．実験より，提案手法の有効性を実証した．


An efficient deletion method for a minimal prefix double array

A minimal prefix (MP) double array is an efficient data structure for a trie. However, the space efficiency of the MP double array is degraded by deletion. This paper presents a fast and compact adaptive deletion algorithm for the MP double array. The presented method is implemented with C.

最小接頭辞ダブル配列はトライを実現するためのデータ構造の一種であり，高速な検索と記憶量のコンパクト性を併せ持つ．しかし，最小接頭辞ダブル配列の空間効率はデータの更新毎に大きく低下する問題がある．本研究では，最小接頭辞ダブル配列に対する効率的なキー削除アルゴリズムを提案する．


A compact static double-array keeping character codes

A trie represented by a double-array enables us to search a key fast with a small space. However, the double-array uses extra space to be updated dynamically. This paper presents a compact structure for a static double-array. The new structure keeps character codes instead of indices in order to compress elements of the double-array. In addition, the new structure unifies common suffixes and consists of less elements than the old structure. Experimental results for English keys show that the new structure reduces space usage of the double-array up to 40%.

ダブル配列のトライは，高速かつコンパクトに実現するデータ構造であるが，動的に更新されるため，余分なスペースができてしまう．本論文では，静的なダブル配列ででコンパクトなデータ構造を提案する．新しいデータ構造は，ダブル配列の要素を圧縮するために，索引ではなく文字コードを使用する．加えて，共通接尾辞を併合し，従来法より少ない要素から構成される．英単語を用いた実験より，提案手法の空間使用は，従来法の40%となった．


Automatic building of new Field Association word candidates using search engine

Readers can know the subject of many document fields by reading only some specific Field Association words. Document fields can be decided efficiently if there are many FA words and if the frequency rate is high. This paper proposes a method for automatically building new FA words. A WWW search engine is used to extract FA word candidates from document corpora. New FA word candidates in each field are automatically compared with previously determined FA words. From the experiential results, our new system can automatically appended around 44% of new FA words.

読者は，複数の分野連想語を見るだけで，その文章の分野を知ることができる．分野連想語の種類が多く，頻度が高ければ，文章の分野を効率的に決定できる．本論文では，新しい分野連想語を自動的に構築する手法を提案する．WWWサーチエンジンを用いて分野連想語の候補を抽出し，以前の分野連想語と比較することにより決定する．実験より，新しい手法は自動的に新しい分野連想語を44%増加することができた．


接頭辞ダブル配列における空間効率を低下させないキー削除法

接頭辞ダブル配列における空間効率を低下させないキー削除法

Minimal Prefix (MP) double-array represents a trie with two advantages - a fast retrieval and a compact dictionary. However, a key deletion produces empty elements and degrades the space efficiency of MP double-array. In addition, the deletion speed of MP double-array is degraded by the key deletion because the deletion time depends on the number of empty elements. This paper presents an efficient deletion method for MP double-array. The method dynamically removes keys from MP double-array without increasing empty elements. From experimental results for the key set which consists of 100,000 keys, it turned out that the presented method is about 17-460 times faster than the conventional method and maintains high space efficiency.

接頭辞ダブル配列はトライを高速かつコンパクトに実現するデータ構造である．しかし，キーの削除によって配列中に未使用の要素が蓄積し，空間効率が低下するという欠点がある．また，更新時間が未使用要素の数に依存するため，削除による空間効率の低下は更新時間の悪化にもつながる．本稿では，未使用要素を増加させることなく接頭辞ダブル配列からキーを削除する手法を提案する．EDR電子化辞書の日英単語各10万件に対する実験により，提案法は従来法と比べて約17-460倍高速であり，高い空間効率を維持することが実証された．

Transactions of Information Processing Society of Japan


An automatic filtering method for field association words by deleting unnecessary words

Generally, humans can recognize fields such as <Sports> or <Politics> based on specific words called Field Association (FA) words in documents. The traditional method causes misleading redundant words (unnecessary words) to be registered because the quality of the resulting FA words depends on learning data pre-classified by hand. This paper propose two criteria: deleting unnecessary words with low frequencies, and deleting unnecessary words using category information. Moreover, using the proposed criteria unnecessary words can be deleted from the FA words dictionary created by the traditional method. Experimental results showed that precision and F-measure were improved by 26% and 15%, respectively.

一般に人は文書中の分野連想語と呼ばれる特定の単語を基に<スポーツ>や<政治>といった分野を認識できる．従来手法では分野連想語の質が人手による学習データに依存するため，不要語を登録してしまう．本論文は，低頻度の不要語の削除とカテゴリー情報を用いた不要語を削除する手法を提案する．さらに，従来法で作成された分野連想語辞書から提案法により不要語を削除する．実験結果から，精度とF値がそれぞれ26%と15%改善された．

International Journal of Computer Mathematics


A Sentence Classification Technique Using Intention Association Expressions

Although there are many text classification techniques depending on the vector space, it is difficult to detect the meaning related to the user's intention (complaint, encouragement, request, invitation, etc.). We present a technique for determining the speaker's intention for sentences in conversation. Intention association expressions are introduced, and formal descriptions with weights are defined using these expressions to construct an intention classification. A deterministic multi-attribute pattern-matching algorithm is used to determine the intention class efficiently. In simulation results for 681 email messages of 5,859 sentences, the multi-attribute pattern-matching algorithm is about 44.5 times faster than the Aho and Corasick method.

ベクトル空間に依存する多くの文書分類手法が存在するが，ユーザーの意図を検出するのは難しい．本論文では，会話文における話者の意図決定手法を提案する．意図分類の構築のために，意図連想表現を導入して，形式的な記述に重みを定義する．効率的な意図クラス決定のために決定論的な多属性照合アルゴリズムを使用する．計5,859文の電子メール681文書でのシミュレーション結果から，多属性照合アルゴリズムはAC法より約44.5倍高速だった．


A Method of Extracting and Evaluating Good and Bad Reputations for Natural Language Expressions

It is difficult to extract good and bad reputations of users from texts written in natural language. This paper presents a method of determining these reputations in commodity review sentences. Multi-attribute rule is introduced to extract the reputations from sentences, and four-stage-rules are defined in order to evaluate good and bad reputations. From simulation results for 2,240 review comments, it is verified that the multi-attribute pattern matching algorithm is 63.1 times faster than the Aho and Corasick method. The precision and recall of extracted reputations for each commodity are 94% and 93% respectively.

自然言語で書かれた文章からユーザーの好不評表現を抽出することは難しい．本論文では，商品レビュー文中のこれらの評判を決定する手法を提案する．文から評判表現を抽出する多属性ルールを定義し，好不評表現を評価する4段階のルールを定義する．2,240のレビューコメントを用いたシミュレーション結果から多属性パターンマッチングはAC法より63.1倍高速で，適合率，再現率はそれぞれ94%と93%となった．

International Journal of Information Technology & Decision Making


Estimating Sentence Types in Computer Related New Product Bulletins Using a Decision Tree

This paper presents a method to extract information for user's intelligent activity supports from an enormous amount of new product articles related to computers on the Internet. This paper uses a decision tree in order to estimate effective sentence types. From experiments, the effectiveness of the presented method is proved.

本論文は，インターネット上に大量に存在するコンピュータ関連の新製品ニュース記事より，ユーザーの知的活動支援に利用する情報を抽出する手法を提案した．本手法では有効な文タイプを推定するために決定木を用い，実験により提案手法の有効性を実証した．


A High-speed Dynamic Full-Text Search Method by Using Memory Management

This paper proposes an adaptive block management algorithm that is efficient for dynamic data management method. The new method speeds up character string retrieval by first making a full-text search of uni-gram and a full-text search of bi-gram. This paper proposes a method for enhancing the static full-text search system of bi-gram to the dynamic full-text search system of bi-gram.

本研究では，動的にデータを管理するブロック管理アルゴリズムを提案する．提案手法により，文字列を高速に検索することが可能となる．提案手法は静的全文検索を動的全文検索に応用するものである．


Word classification and hierarchy using co-occurrence word information

In the natural language processing system, dictionary is necessary and indispensable because the ability of the entire system is controlled by the amount and the quality of the dictionary. In this paper, the importance of co-occurrence word information in the natural language processing system is described. The classification technique of the co-occurrence word and the co-occurrence frequency is described and the classified group is expressed hierarchically. Moreover, this paper proposes a technique for an automatic construction system and a complete thesaurus. Experimental test operation of this system and effectiveness of the proposal technique is verified.

自然言語処理システムでは，システム全体の性能が辞書の量と質によって制御されるので，辞書は必要不可欠である．本論文では，自然言語処理システムにおける共起情報の重要性を説明し，共起語と共起頻度の分類とグループ階層化手法を説明する．また，シソーラス(統語辞書)の自動構築手法を提案する．実験によりシステムの動作と提案手法の有効性を確認する．


An efficient e-mail filtering using time priority measurement

With the spread of e-mails, it is getting very difficult to find urgent e-mails from a huge amount of received e-mails. This paper presents a method to determine the time priority for e-mail messages. The presented method can classify and rank missing messages with important time information according to time priority measurement automatically. From the simulation results for determination of the time priority, the presented pattern-matching method is about 4 times faster than the traditional string pattern-matching method.

電子メールの普及に伴い，受信した大量のメールの中から緊急の用件を見つけるのが困難になっている．本論文では，電子メールに含まれる時間表現を，多属性のパターンマッチングルールを用いて抽出することにより，メールの優先度を決定する手法を提案する．提案手法により，処理時間が従来のストリングパターンマッチング手法の約4倍に改善することを確認した．


A compression algorithm using integrated record information for translation dictionaries

This paper presents a method of merging individual dictionaries into the generalized dictionary. It enables us to reduce the total dictionary size and to expand the usage of individual dictionaries to that of the other applications. A fast trie structure, called a double-array structure is introduced and its compression scheme is proposed by replacing long strings into corresponding leaf node numbers of the Trie. Although the size of the presented records grows, the total number of them is extremely decreased by merging common information. The presented method is evaluated by the observation experimental results for nine dictionaries show that new method is more efficient than previous ones.

本論文は個別の辞書を1つの辞書に統合する手法を提案する．統合により辞書の総サイズを減少でき，個別の辞書の利用を他のアプリケーションに拡張できる．ダブル配列構造を利用して，長い文字列をトライの対応する葉ノード番号に置き換えることで圧縮する技術を提案する．レコードサイズは増加するが，共通の情報を併合することによりその総数は非常に減少する．提案法は従来法より効率的であることを，9の辞書を用いた実験結果より評価する．


A New Compression Method of Double Array for Compact Dictionaries

Double array is a well-known data structure to implement the trie, which is a widely used approach to retrieve strings in a dictionary. This paper presents a compression method by dividing the trie constructed into several pieces (pages). This compression method enables us to reduce the number of bits representing entries of the double array. The obtained trie must trace to the pages that cause slow retrieval time, because of a state connection. Experimental results applying for a large set of keys show that the storage capacity has been reduced to 50%. Moreover, our new approach has the same retrieval speed as the old one.

ダブル配列は，辞書内の単語を検索するためのトライを実装するデータ構造として，よく知られているが，大規模なキー集合を扱うとき，サイズが大きくなってしまう問題がある．本論文では，一つのダブル配列を複数の小さいトライに分割することにより，状態番号を表すのに必要となるサイズを小さくし，ダブル配列全体を圧縮する手法を提案した．実験により，ダブル配列の高速性を失うことなく，50%に圧縮できることを実証した．

International Journal of Computer Mathematics


Fast and compact updating algorithms of a double-array structure

As a fast and compact data structure for a trie, a double-array is presented. However, the insertion time is not faster than other dynamic retrieval methods because the double-array is a semi-static retrieval method that cannot treat high frequent updating. Further, the space efficiency of the double-array degrades with the number of deletions because it keeps empty elements produced by deletion. This paper presents a fast insertion algorithm by linking empty elements to find inserting positions quickly and a compression algorithm by reallocating empty elements for each deletion. From the simulation results for 100 thousands keys, it turned out that the insertion time and the space efficiency are achieved.

トライの高速でコンパクトなデータ構造としてダブル配列が提案されている．しかし，ダブル配列は高頻度の更新を考慮しない準静的な検索手法であるため，他の動的更新手法より追加時間が遅い．さらに，削除時に空要素を保持するので，削除数に応じて空間効率が下がる．本論文は，空要素リンクによる高速追加手法と，削除時の空要素再配置による圧縮手法を提案する．10万件キーによる実験結果から，追加時間と空間効率が達成された．


An Improvement Key Deletion Method for Double-Array Structure using Single-nodes

The drawback of the double-array is that the space efficiency degrades by empty elements produced in key deletion. The space efficiency of old method is low for high frequent deletion and deletion takes much time because the cost depends on the number of the empty elements. This paper presents a fast and compact deletion method by using the property of nodes of single.

ダブル配列構造の欠点は，キー削除により空間効率が低下することである．従来手法の空間効率はキー削除の回数に比例して，情報を持たない無駄なノードが増加する．本研究では，トライのシングルノードに着目し，この問題を解決する高速かつコンパクトな削除手法を提案する．


A Fast and Compact Elimination Method of Empty Elements from a Double-Array Structure

This paper presents a fast and compact elimination method of empty elements using properties of the trie nodes that have no siblings. The present elimination method is implemented by C language. From simulation results for large sets of keys, the present elimination method is about 30-330 times faster than the conventional elimination method and maintains high space efficiency.

本研究では，トライのうち，兄弟ノードがないノードを用いた効率的な空白要素の除去手法を提案する．提案手法をC言語で実装し，実験を行った．従来の除去手法より30-330倍高速に処理でき，高い空間効率を実現できることを示した．


Documents similarity measurement using field association terms

This paper outlined a new text manipulation system FA-Sim that is useful for retrieving information in large heterogeneous texts and for recognizing content similarity in text excerpts. FA-Sim measures texts similarity by using specific field association (FA) terms instead of by comparing all text information. Similarity between texts is faster and higher by using FA-Sim than other two analysis methods. Therefore, Recall and Precision significantly improved by 39% and 37% over these two traditional methods.

本論文は，テキスト抜粋による内容認識や大規模テキスト情報検索に有用なテキスト処理システムFA-simを提案する．FA-simはすべてのテキスト情報を比較する代わりに分野連想語を用いてテキストの類似度を測る．FA-simによるテキスト間の類似度は，他の2つの従来法より高速で高精度である．再現率と精度は，従来法よりそれぞれ39%と37%向上した．


ダブル配列におけるキー削除の効率化手法

ダブル配列におけるキー削除の効率化手法

ダブル配列構造の欠点はキーの削除によって生じる未使用要素により空間効率が低下する点である．本論文ではトライの兄弟を持たない節が多く，これらの節の遷移は容易に変更できるという特徴を利用し，削除を連続した場合でも空間使用率と削除速度を悪化させない効率的なキー削除手法を提案する．10万語の英単語に対する実験より，削除を連続した場合でも98%以上の空間使用率を維持でき，従来手法より約300倍高速に削除できることを実証した．

Transactions of Information Processing Society of Japan


A New Method for Selecting English Field Association Terms of Compound Words and Its Knowledge Representation

This paper presents a strategy for building a morphological machine dictionary of English that infers meaning of derivations by considering morphological affixes and their semantic classification. This paper also proposes an efficient method for selecting compound Field Association terms from a large pool of single FA terms. For single FA terms, five levels of association are defined and two ranks are defined. About 85% of redundant compound FA terms can be removed effectively by using levels and ranks proposed in this paper. Recall averages of 60-80% are achieved. The proposed methods are applied to 22,000 relationships between verbs and nouns extracted.

本論文は，接辞や意味分類を用いて，英語の形態素辞書を構築する手法を提案する．さらに，大規模な短単位の分野連想語から複合語の分野連想を選択する効率的な手法を提案する．関連性を5つの分野に分け，2つのランクを定義した．実験より，約85%の無駄な複合語を削除することができた．再現率は60∼80%となった．抽出された動詞と名詞より，22,000の関係性を抽出することができ，提案手法の有効性を実証した．


2次記憶上のダブル配列の効率的検索法

2次記憶上のダブル配列の効率的検索法

キー検索技法であるダブル配列は，大規模なキー集合を扱うとき，サイズが大きくなってしまう問題がある．本論文では，ダブル配列を2次記憶上に格納した時に，記憶量も圧縮し，更に少ない主記憶領域で効率的に検索できる手法を提案する．実験により従来法に比べ50%に圧縮されることが分かった．

The Transactions of the Institute of Electronics, Information and Communication Engineers D-I

電子情報通信学会論文誌(D-I)


An Efficient Trie Construction for Natural Language Dictionaries

When the total number of nodes of the trie becomes large, it takes a lot of spaces for a huge set of keys. This paper presents a compression method for these long strings by using trie arc for single words. The theoretical and experimental observations show the presented method is more practical than traditional methods.

トライに長い単語や複合語を登録すると，空間使用率が悪くなると言う問題が知られている．本論文では，単語のリンク情報を用いて複合語を圧縮して登録する手法を提案する．理論的評価と実験を行い，本手法の有効性を確認した．

International Journal of Computer Mathematics


ダブル配列における動的更新の効率化アルゴリズム

ダブル配列における動的更新の効率化アルゴリズム

キー検索技法の一つであるダブル配列は，動的更新の速度が問題となっている．本論文では，追加を高速化する手法と，削除時に生じる未使用要素の詰め直しを行う手法を提案する．10万語のキーを用いた実験を行い，本手法の有効性を実証した


A Method for Improving Full Text Search Using Signature Files

Signature files are one of indexes for a fast full text search, but they causes a problem to degrade the search speed by false drops. This paper presents a method to reduce the problem by appearance ratio which is computed by scanning documents.

シグネチャファイルは，高速な全文検索のために考案された索引のひとつであるが，フォールスドロップによる検索速度低下の問題が知られている．本論文では，文書を一度走査し，文字列の出現確率を求め，この出現確率を利用して検索速度の低下をおさえる手法を提案した．

International Journal of Computer Mathematics


Fast insertion methods of a double-array structure

A double-array structure degrades the speed of insertion for a large set of keys. This paper implements two methods; one is to skip elements to be checked and the other is to produce the linkage among empty elements, and proves that insertion by those two methods is faster than insertion by a traditional method.

ダブル配列は，大量のキー集合に対する追加処理のスピードが遅い．本論文では，特定の要素をスキップする手法と，空き要素をリンクする手法の2種類の追加手法を実装し，従来法よりも高速に追加を行えることを実証した．


Conceptual and Quantitative Representations of Time Expressions

In natural language processing systems, it is very important to understand the meaning of time expressions. This paper proposes a method for understanding time expressions. For components of which time expressions consist, 31 concepts are introduced. Formal representations for these concepts are defined and an algorithm of analyzing the meaning of time expressions is proposed. The representation includes both conceptual and quantitative aspects in comparison with traditional approaches. An algorithm for translating time expressions into the corresponding formal representation is presented. Experiments for about 2,000 time expressions show that the proposed method yields correct interpretation in about 93%.

自然言語処理システムでは，時間表現の意味理解は非常に重要である．本論文では，時間表現を理解する手法を提案する．時間表現を構成する要素のため，31個の概念を紹介する．これらの概念のための形式表現を定義し，時間表現の意味を解析する手法を提案した．時間表現は，概念と数量の表現を含んでいる．また，時間表現を形式的な行現に変換するアルゴリズムの提案も行なった．実験の結果，提案手法の有効性を実証した．

Computer Processing of Oriental Languages


An Efficient Representation for Implementing Finite State Machines Based on the Double-Array

When finite state machines are implemented, a problem is space efficiency. This paper proposes the extended double-array structure so that is can be applicable to general finite state machines and be operated dynamically with the insertion and the deletion of a state transition. The presented method has been evaluated by theoretical observations, and its space efficiency is verified in the experiment.

有限状態機械を実装する場合，空間効率が問題となる．本論文では，ダブル配列を用いて有限状態機械を実現する手法を提案し，状態の追加，削除を行う手法も提案した．理論的評価と実験を行い，本手法により空間効率が改善することを実証した．


Similarity measures using negative weight and its application to word similarity

A "term weighting" is a useful technique for keyword extraction and document classification. The traditional approach depends on high frequency terms. This paper presents a new weighting method that depends on low frequency terms. In this paper, word similarity for typical verbs and objects is focused as an example for the application field. The proposed method is applied to 11,000 relationships between verbs and nouns extracted from a large tagged corpus. By using this new method both recall and precision have improved by 33% and 18% respectively.

単語への重み付けは，キーワード抽出や文書分類でよく使われている．従来法では頻度が高い語が使われているが，本論文では，頻度が低い語を用いた新しい重み付け手法を提案する．動詞と目的語の単語類似度はアプリケーション分野の例として焦点を当てる．提案手法は，動詞と名詞の11,000個の関係性を用いる．実験により，従来法に比べ，提案手法の再現率は33%，適合率は18%の向上が見られた．


A Document Classification Method by using Field Association Words

Although there is much research of text classification based on vector spaces using word information in the whole text, generally humans can recognize the field by finding the specific words. In this paper, such words are called a field association (FA) word that can be directly related to the field classification. This paper presents an early field un- derstanding method using FA words. Five criteria of FA words are defined for hier- archical fields and a method of extracting shorter FA words of compound words is proposed. The presented approach is estimated by the simulation results of 140 fields' text files

文書内の単語情報によるベクトル空間を用いた文書分類の研究は多く存在するが，一般的に人間は特定の後を見つけるだけで分野を判定できる．本論文では，そのように直接分野分類できる単語を分野連想語と呼び，分野連想語を使って早期に分野を判定できる手法を提案する．分野連想語の5つの基準で，階層的な分野を定義し，最も短い複合語の分野連想語を抽出する手法を提案する．140の分野を用いてシミュレーションをおこなった．


An Efficient Method of Determining Field Association Terms of Compound Words

複合語の分野連想語の効率的決定法

本論文では，短単位語の分野連想語情報を利用して，非常に多く造語される複合連想語を効率的に決定する手法を提案し，180分野の学習データを用いた実験により，提案手法の有効性を評価した．また，構築された連想語が文書断片の分野決定に有効であることも示した．


A Link Trie Structure of Storing Multiple Attribute Relationships for Natural Language Dictionaries

Word relation is primitive knowledge and it is very useful for natural language processing systems. In the traditional systems, although each knowledge dictionary is constructed in separation, recent natural language applications become more complex by integrating the above multi-attribute relationships. This paper presents an efficient data structure by introducing a trie that can define the linkage among their leaves. Theoretical observations show that the worst-case time complexity of retrieving multi-attribute relationships is a constant. From the simulation results, it is shown that the presented method is 1/3 smaller than the competitive methods.

単語の関係は自然言語処理システムでよく利用される基本的な知識である．伝統的なシステムでは，各知識辞書を個別に構築するが，最近はそれら多属性関係を統合した複雑なシステムとなっている．本論文はトライの葉間にリンクを定義できる効率的データ構造を提案する．理論的評価で多属性関係検索の最悪時間が一定であることを示す．実験結果から，比較手法に対して1/3に縮小することを示した．

International Journal of Computer Mathematics


日本語時間表現の一解釈法

日本語時間表現の一解釈法

本論文では，自然言語による時間表現を意味解釈するために，意味解釈を時点，時点区間などの概念に分類し，時間表現に対する形式表現を定義した．また，形態素列からなる時間表現から形式表現に変換するアルゴリズムを提案し，実験により提案手法の有効性を実証した．

Transactions of Information Processing Society of Japan


Efficient Controlling of Parsing-Stack Operations for LR Parsers

This paper presents a new method of LR parsing based on the distinction of stack states and non-stack states. Non-stack states are states, which do not need to be pushed into the LR parsing stack, and stack states are states to be pushed into it. By using some properties based on the stack-controlling LR parser defined here, the parsing speed and the size of parsing tables can be remarkably improved and their improvement includes the traditional method eliminating unit productions. By empirical observations for a variety of programming languages, the efficiency is verified. Extending it to the generalized LR parsers for natural language is also discussed.

本論文では，スタック状態と非スタック状態の違いを基としたLRパーサーを提案した．非スタック状態は，LRパーサースタックに追加する必要のない状態であり，スタック状態は，追加される状態である．スタックを管理するLRパーサーを基にした属性を用いて，速度とサイズを改善し，従来法との比較を行った．様々なプログラミング言語による実験により，有効性を確認した．自然言語における一般的なLRパーサーの拡張性についても議論した．


A Fast Retrieving Algorithm of Hierarchical Relationships Using Trie Structures

This paper presents a faster method to determine the hierarchical relationships by using trie structures. The worst-case time complexity of determining relationships by the presented method could be remarkably improved for the one of linear (or sequential) searching, which depends on the number of concepts in the case slot. From the simulation result, it is shown that the presented algorithm is 6 to 30 times faster than linear searching, while keeping the smaller size of tries.

本論文はトライを用いた階層関係の高速検索手法を提案する．提案手法による検索の時間計算量は格スロットの概念数に依存する線形検索に対して著しく改善された．実験結果から，提案手法はトライのサイズを小さく維持したまま6∼30倍高速になることがわかった．


A Fast Method of Determining Weighted Compound Keywords from Text Databases

This paper presents a technique for storing compound keywords about both short component keywords and long component keywords by extending Aho and Corasick (AC) string pattern matching machine. By theoretical analysis, it is verified that the total cost of the extended AC machine becomes O(n+k) in comparison with the total cost O(3n) of the original AC machine. By simulation results for 38 Japanese text files, it is shown that the extended AC machine is about three to six times faster than the original AC machine in SC and LC keyword processing

本論文では，キーワード抽出における複合語の効率的な検出方法を複数キーワードの文字列照合法であるAC(Aho and Corasic)法を利用して提案した．理論的評価により，従来法がO(3n)であったのに対し本手法では，長O(n+k)となることが確認できた．また，日本語の38ファイルを用いた実験により，従来法より3∼6倍高速になることが確認できた


A Fast Algorithm of Retrieving Common Sentences

Inverted filing is a well-known approach for retrieving common sentences, but there are some problems when storing a huge number of sentences. They arise when the intersection is computed for large postings indexed by terms, or keywords. Moreover, disk access for postings also takes a lot of time in this situation. This paper presents a technique for the storing of multi-stages of postings and retrieving them partly in order to compute efficiently the intersection between postings for the requested terms. From the simulation results, it is shown that the presented algorithm is 6 to 88 times faster than the traditional ap- proach

用例文検索では，転地ファイルがよく知られるが，対象が大規模な場合，文書ごとに索引が作られることや，ディスクアクセスに時間がかかる等の問題がある．本論文では，用例文を検索する場合に，多くの要求から目的とする文を高速に絞り込む手法を提案した．ビットベクトルによる複合的な論理演算を提案し，約1億文のデータに対しても実用的な絞り込み時間となることを示した．用例文を検索する場合に，多くの要求から目的とする文を高速に絞り込む手法を提案した．ビットベクトルによる複合的な論理演算を提案し，約1億文のデータに対しても実用的な絞り込み時間となることを示した．


格構造解析における概念階層の効率的判定アルゴリズム

格構造解析における概念階層の効率的判定アルゴリズム

本論文では，概念階層のデータ構造にトライ構造を導入して，判定効率を向上させる手法を提案する．また，本手法では複数の用言の格構造を1つのトライに併合して格納するので，トライ検索後に目的とする用言を効率的に確定する手法も提案する．同音語とEDRの共起データに対する実験結果により，本手法は6から25倍高速化されることが分かった．


大規模文書データに対する用例文の効率的検索アルゴリズム

大規模文書データに対する用例文の効率的検索アルゴリズム

大量の用例文データから複数の索引要求に共通する用例文を検索する手法は，文書管理システムにおいて必要不可欠な技法である．本論文では，索引が指定する複数の文番号を文番号列とするとき，多くの索引要求があり，しかも索引に対する文番号列が非常に長くなる場合でも，目的とする用例文を高速に絞り込めるアルゴリズムを提案する．


A method for Understanding Intentions of Indirect Speech-Act in Natural Language Interfaces

自然言語インタフェースにおける間接発話分の意図理解法

The Transactions of the Institute of Electronics, Information and Communication Engineers D-II

電子情報通信学会論文誌(D-II)


An Incremental Algorithm for String Pattern Matching Machines

International Journal of Computer Mathematics