論文 - 関 和広
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個人の発言と思想に基づくコミュニティ内の偉人の理念を考慮した対話生成
末吉 将也, 北畑 哲也, 関 和広, 灘本 明代
第17回データ工学と情報マネジメントに関するフォーラム 2025年3月
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コミュニティ内の偉人の理念を考慮したスピーチ生成
北畑 哲也, 末吉 将也, 関 和広, 灘本 明代
第17回データ工学と情報マネジメントに関するフォーラム 2025年3月
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How to Interpret an Economic Index? Generating Reports with Topic Sentiment Analysis 査読あり
Kazuhiro Seki
Proceedings of the 13th International Conference on Building and Exploring Web Based Environments 9 - 10 2025年3月
担当区分：筆頭著者, 最終著者, 責任著者
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Refining Sentiment Predictions: Obtaining an Unbiased Business Sentiment Index from Japanese Newspapers 査読あり
Kazuhiro Seki
International Journal of Asian Language Processing 33 ( 2 ) 2350015 2023年12月
担当区分：筆頭著者, 最終著者, 責任著者
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Topic-Sentiment Analysis of Central Bank Press Conferences: BOJ Case Study 査読あり
Kazuhiro Seki, Masahiko Shibamoto, and Takashi Kamihigashi
Proceedings of the 5th Financial Narrative Processing Workshop 2861 - 2865 2023年12月
担当区分：筆頭著者, 責任著者
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Turning News Texts into Business Sentiment 査読あり
Kazuhiro Seki
Proceedings of the 44th European Conference on Information Retrieval (ECIR 2022) 311 - 315 2022年4月
担当区分：筆頭著者, 最終著者, 責任著者
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News-based business sentiment and its properties as an economic index 査読あり 国際誌
Kazuhiro Seki, Yusuke Ikuta, Yoichi Matsubayashi
INFORMATION PROCESSING & MANAGEMENT 59 ( 2 ) 2022年3月
担当区分：筆頭著者, 責任著者 出版者・発行元：ELSEVIER SCI LTD
This paper presents an approach to measuring business sentiment based on textual data. Business sentiment has been measured by traditional surveys, which are costly and time-consuming to conduct. To address the issues, we take advantage of daily newspaper articles and adopt a self-attention-based model to define a business sentiment index, named S-APIR, where outlier detection models are investigated to properly handle various genres of news articles. Moreover, we propose a simple approach to temporally analyzing how much any given event contributed to the predicted business sentiment index. To demonstrate the validity of the proposed approach, an extensive analysis is carried out on 12 years' worth of newspaper articles. The analysis shows that the S-APIR index is strongly and positively correlated with established survey-based index (up to correlation coefficient r = 0.937) and that the outlier detection is effective especially for a general newspaper. Also, S-APIR is compared with a variety of economic indices, revealing the properties of S-APIR that it reflects the trend of the macroeconomy as well as the economic outlook and sentiment of economic agents. Moreover, to illustrate how S-APIR could benefit economists and policymakers, several events are analyzed with respect to their impacts on business sentiment over time.
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Cross-lingual text similarity exploiting neural machine translation models 査読あり
Kazuhiro Seki
Journal of Information Science 47 ( 3 ) 404 - 418 2021年6月
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経済ニュースによる景況感指数の足元予測 査読あり
関和広, 生田祐介
情報処理学会論文誌 62 ( 5 ) 1288 - 1297 2021年5月
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S-APIR: News-Based Business Sentiment Index 査読あり
Kazuhiro Seki, Yusuke Ikuta
Proceedings of the 24th European Conference on Advances in Databases and Information Systems 2020年8月
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Effectiveness and Efficiency for Document Clustering in Biomedicine 査読あり 国際共著
Kazuhiro Seki, Michael Ortiz, Javed Mostafa
Proceedings of the 10th International Workshop on Biomedical and Health Informatics 1620 - 1623 2019年11月
共著
担当区分：筆頭著者, 責任著者
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Dynamic Cluster-based Retrieval and Discovery for Biomedical Literature 査読あり 国際共著
Michael Ortiz, Heejun Kim, Mika Wang, Kazuhiro Seki, Javed Mostafa
Proceedings of the 10th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB) 2019年9月
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Estimating Business Sentiment from News Texts 査読あり
Kazuhiro Seki, Yusuke Ikuta
Proceedings of the 2nd IEEE Artificial Intelligence and Knowledge Engineering 2019年6月
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担当区分：筆頭著者, 責任著者
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On Cross-Lingual Text Similarity Using Neural Translation Models 査読あり
Kazuhiro Seki
Journal of Information Processing 27 315 - 321 2019年
単著
担当区分：筆頭著者, 最終著者, 責任著者
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Exploring Neural Translation Models for Cross-Lingual Text Similarity 査読あり
Kazuhiro Seki
Proceedings of the 27th ACM International Conference on Information and Knowledge Management (CIKM) 1591 - 1594 2018年10月
単著
担当区分：筆頭著者, 最終著者, 責任著者
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Construction and Application of Sentiment Lexicons in Finance 招待あり 査読あり
Kazuhiro Seki, Masahiko Shibamoto
International Journal of Multimedia Data Engineering and Management 9 ( 1 ) 22 - 35 2018年1月
共著
担当区分：筆頭著者, 責任著者
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Constructing Financial Sentiment Lexicons by Integrating Textual and Time-Series Data 査読あり
Kazuhiro Seki and Masahiko Shibamoto
Proceedings of the 2017 IEEE International Conference on Information Reuse and Integration 2017年8月
共著
担当区分：筆頭著者
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Financial Sentiment Orientation of Word Combinations 査読あり
Kazuhiro Seki
Proceedings of the 20th International Conference on Knowledge Engineering and Knowledge Management 2016年11月
単著
担当区分：筆頭著者
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Leveraging Temporal Properties of News Events for Stock Market Prediction 査読あり
Akira Yoshihara, Kazuhiro Seki, and Kuniaki Uehara
Artificial Intelligence Research 2016年1月
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医療用語資源の語彙拡張と診療情報抽出への応用 査読あり
東山翔平，関和広，上原邦昭
自然言語処理 22 ( 2 ) 77 - 106 2015年6月
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Detecting Vital Documents Using Negative Relevance Feedback in Distributed Realtime Computation Framework 査読あり
Shun Kawahara, Kazuhiro Seki, and Kuniaki Uehara
Proceedings of the 2015 Conference of the Pacific Association for Computational Linguistics (PACLING 2015) 2015年5月
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Cost-Sensitive Structured Perceptron Incorporating Category Hierarchy for Named Entity Recognition 招待あり 査読あり
Shohei Higashiyama, Mathieu Blondel, Kazuhiro Seki, and Kuniaki Uehara
Journal of Information and Communication Technology 2015年5月
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Hypothesis Discovery Exploiting Closed Chains of Relations 査読あり
Kazuhiro Seki
Transactions on Large-Scale Data- and Knowledge-Centered Systems 2015年
単著
担当区分：筆頭著者
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Detecting Vital Documents in Massive Data Streams 査読あり
Shun Kawahara, Kazuhiro Seki, and Kuniaki Uehara
Open Journal of Web Technologies 2015年
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Hypothesis Discovery Exploiting Closed Chains of Relations.
Kazuhiro Seki
Trans. Large-Scale Data- and Knowledge-Centered Systems 22 145 - 164 2015年
単著
出版者・発行元：Springer
その他リンク： http://dblp.uni-trier.de/db/journals/tlsdkcs/tlsdkcs22.html#journals/tlsdkcs/Seki15
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Predicting the Trend of the Stock Market by Recurrent Deep Neural Networks 査読あり
Akira Yoshihara, Kazuki Fujikawa, Kazuhiro Seki, and Kuniaki Uehara
Proceedings of the 13th Pacific Rim International Conference on Artificial Intelligence (PRICAI-2014) 2014年12月
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A Cost-Sensitive Approach to Named Entity Recognition with Category Hierarchy 査読あり
Shohei Higashiyama, Blondel Mathieu, Kazuhiro Seki, and Kuniaki Uehara
International Conference on Computer and Information Sciences 2014年6月
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Time-Aware Latent Concept Expansion for Microblog Search 査読あり
Taiki Miyanishi, Kazuhiro Seki, and Kuniaki Uehara
8th International AAAI Conference on Weblogs and Social Media (ICWSM 2014) 2014年6月
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マイクロブログ文書の選択による適合フィードバックを用いた疑似適合フィードバックの検索性能改善 査読あり
宮西大樹，関和広，上原邦昭
情報処理学会論文誌 2014年5月
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三段論法的パターンに着目した解釈容易な仮説の生成規則獲得と順位付け 査読あり
関和広，上原邦昭
情報処理学会論文誌 2014年4月
共著
担当区分：筆頭著者
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Predicting Stock Market Trends by Recurrent Deep Neural Networks.
Akira Yoshihara,Kazuki Fujikawa,Kazuhiro Seki,Kuniaki Uehara
PRICAI 2014: Trends in Artificial Intelligence - 13th Pacific Rim International Conference on Artificial Intelligence, Gold Coast, QLD, Australia, December 1-5, 2014. Proceedings 759 - 769 2014年
共著
出版者・発行元：Springer
その他リンク： http://dblp.uni-trier.de/db/conf/pricai/pricai2014.html#conf/pricai/YoshiharaFSU14
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Interactive Disaster Information Search System for Microblog by Minimal User Feedback 査読あり
Sayaka Kitaguchi, Taiki Miyanishi, Kazuhiro Seki, and Kuniaki Uehara
9th Asia Information Retrieval Societies Conference (AIRS 2013) 2013年12月
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Parallel Distributed Trajectory Pattern Mining Using Hierarchical Grid with MapReduce 招待あり 査読あり
Kazuhiro Seki, Ryota Jinno, and Kuniaki Uehara
International Journal of Grid and High Performance Computing 2013年12月
共著
担当区分：筆頭著者
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Developing ML-based Systems to Extract Medical Information from Japanese Medical History Summaries 査読あり
Shohei Higashiyama, Kazuhiro Seki, and Kuniaki Uehara
First Workshop on Natural Language Processing for Medical and Healthcare Fields 2013年11月
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A Shape-based Similarity Measure for Time Series Data with Collaborative Ensemble Learning 査読あり
Tetsuya Nakamura, Keishi Taki, Hiroki Nomiya, Kazuhiro Seki, and Kuniaki Uehara
Pattern Analysis and Applications 2013年11月
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Improving Pseudo-Relevance Feedback via Tweet Selection 査読あり
Taiki Miyanishi, Kazuhiro Seki, and Kuniaki Uehara
22nd ACM International Conference on Information and Knowledge Management (CIKM 2013) 2013年11月
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Agglomerative Co-Clustering for Synonymous Phrases Based on Common Effects and Influences 査読あり
Koji Kumanami, Kazuhiro Seki, and Kuniaki Uehara
IEEE Big Data 2013 Workshop on Scalable Machine Learning 2013年10月
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Block Coordinate Descent Algorithms for Large-scale Sparse Multiclass Classification 査読あり
Mathieu Blondel, Kazuhiro Seki, and Kuniaki Uehara
Machine Learning 2013年10月
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Supervised Hypothesis Discovery Using Syllogistic Patterns in the Biomedical Literature 査読あり
Kazuhiro Seki, and Kuniaki Uehara
23rd International Joint Conference on Artificial Intelligence (IJCAI 2013) 2013年8月
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担当区分：筆頭著者
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NegFinder: A Web Service for Identifying Negation Signals and Their Scopes 査読あり
Kazuki Fujikawa, Kazuhiro Seki, and Kuniaki Uehara
IPSJ Transactions on Bioinformatics 2013年7月
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マイクロブログ検索のための時間情報と非時間情報を統合したクエリ拡張 査読あり
宮西大樹，関和広，上原邦昭
情報処理学会論文誌 2013年4月
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Learning Non-Linear Classifiers with a Sparsity Constraint using L1 Regularization 査読あり
Mathieu Blondel, Kazuhiro Seki, and Kuniaki Uehara
28th Annual ACM Symposium On Applied Computing (SAC 2013) 2013年3月
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Combining Recency and Topic-Dependent Temporal Variation for Microblog Search 査読あり
Taiki Miyanishi, Kazuhiro Seki, and Kuniaki Uehara
35th Annual European Conference on Information Retrieval (ECIR 2013) 2013年3月
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カテゴリ階層を考慮した構造化パーセプトロンによる固有表現抽出 査読あり
東山翔平，ブロンデルマチュー，関和広，上原邦昭
情報処理学会論文誌：数理モデル化と応用 2013年
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Block coordinate descent algorithms for large-scale sparse multiclass classification.
Mathieu Blondel,Kazuhiro Seki,Kuniaki Uehara
Machine Learning 93 ( 1 ) 31 - 52 2013年
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A shape-based similarity measure for time series data with ensemble learning.
Tetsuya Nakamura,Keishi Taki,Hiroki Nomiya,Kazuhiro Seki,Kuniaki Uehara
Pattern Anal. Appl. 16 ( 4 ) 535 - 548 2013年
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Parallel Distributed Trajectory Pattern Mining Using MapReduce 査読あり
Ryota Jinno, Kazuhiro Seki, and Kuniaki Uehara
4th IEEE International Conference on Cloud Computing Technology and Science (CloudCom 2012) 2012年12月
共著
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Generating Interpretable Hypotheses Based on Syllogistic Patterns 査読あり
Takuya Hagimura, Kazuhiro Seki, and Kuniaki Uehara
AAAI-2012 Fall Symposium on Information Retrieval and Knowledge Discovery in Biomedical Text 2012年11月
共著
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A Hybrid Approach to Finding Negated and Uncertain Expressions in Biomedical Documents 査読あり
Kazuki Fujikawa, Kazuhiro Seki, and Kuniaki Uehara
2nd International Workshop on Managing Interoperability and compleXity in Health Systems 2012年10月
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リンク予測を基にした時系列ネットワーク中でのオブジェクトランキング 査読あり
宮西大樹，関和広，上原邦昭
人工知能学会論文誌 2012年3月
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Object ranking in evolutional networks via link prediction
Taiki Miyanishi, Kazuhiro Seki, Kuniaki Uehara
Transactions of the Japanese Society for Artificial Intelligence 27 ( 3 ) 223 - 234 2012年
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出版者・発行元：Japanese Society for Artificial Intelligence
This paper proposes a framework to predict future significance or importance of nodes of a network through link prediction. The network can be of any kind, such as a co-authorship network where nodes are authors and coauthors are linked by edges. In this example, predicting significant nodes means to discover influential authors in the future. There are existing approaches to predicting such significant nodes in a future network and they typically rely on existing relationships between nodes. However, since such relationships are dynamic and would naturally change over time (e.g., new co-authorship continues to emerge), approaches based only on the current status of the network would have limited potentiality to predict the future. In contrast, our proposed approach first predicts future links between nodes by multiple supervised classifiers and applies the RankBoost algorithm for combining the predictions such that the links would lead to more precise predictions of a centrality (significance) measure of our choice. To demonstrate the effectiveness of our proposed approach, a series of experiments are carried out on the arXiv (HEP-Th) citation data set.
DOI： 10.1527/tjsai.27.223
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階層グリッドを用いた四分木探索による移動軌跡データからの並列分散型頻出パターン検出 査読あり
神野良太，熊南昂司，福井聡，関和広，上原邦昭
人工知能学会論文誌 2012年
共著
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L1正則化によるスパース性の制約を用いた非線形分類器の学習 査読あり
ブロンデルマチュー，関和広，上原邦昭
人工知能学会論文誌 2012年
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担当区分：筆頭著者
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文献情報を用いたカーネル法による遺伝子機能アノテーション 査読あり
ブロンデルマチュー，関和広，上原邦昭
情報処理学会論文誌：数理モデル化と応用 2011年11月
共著
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Application of Semantic Kernels to Literature-Based Gene Function Annotation 査読あり
Mathieu Blondel, Kazuhiro Seki, and Kuniaki Uehara
14th International Conference on Discovery Science (DS 2011) 2011年10月
共著
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Tackling Class Imbalance and Data Scarcity in Literature-Based Gene Function Annotation 査読あり
Mathieu Blondel, Kazuhiro Seki, and Kuniaki Uehara
31th annual international ACM SIGIR conference on research and development in information retrieval (SIGIR 2011) 2011年7月
共著
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Hypothesis Ranking Based on Semantic Event Similarities 査読あり
Taiki Miyanishi, Kazuhiro Seki, and Kuniaki Uehara
IPSJ Transactions on Bioinformatics 2011年5月
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Opinionated Document Retrieval Using Subjective Triggers 査読あり
Kazuhiro Seki and Kuniaki Uehara
Journal of the American Society for Information Science and Technology 2011年5月
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担当区分：筆頭著者
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Unsupervised Learning of Stroke Tagger for Online Kanji Handwriting Recognition 査読あり
Mathieu Blondel, Kazuhiro Seki, and Kuniaki Uehara
20th International Conference on Pattern Recognition (ICPR 2010) 2010年8月
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Impact and Prospect of Social Bookmarks for Bibliographic Information Retrieval 査読あり
Kazuhiro Seki, Huawei Qin, and Kuniaki Uehara
10th ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL 2010) 2010年6月
共著
担当区分：筆頭著者
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Hypothesis Generation and Ranking Based on Event Similarities 査読あり
Taiki Miyanishi, Kazuhiro Seki, and Kuniaki Uehara
25th Annual ACM Symposium On Applied Computing (SAC 2010) 2010年3月
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リンク構造とコンテンツを複合的に用いた極少訓練事例によるスプログ検出 査読あり
吉川幹人，佐藤翔平，関和広，上原邦昭
情報処理学会論文誌：データベース 2010年3月
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Finding explicit and implicit knowledge: Biomedical text data mining
Kazuhiro Seki, Javed Mostafa, Kuniaki Uehara
Intelligent Soft Computation and Evolving Data Mining: Integrating Advanced Technologies 370 - 386 2010年
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出版者・発行元：IGI Global
This chapter discusses two different types of text data mining focusing on the biomedical literature. One deals with explicit information or facts written in articles, and the other targets implicit information or hypotheses inferred from explicit information. A major difference between the two is that the former is bound to the contents within the literature, whereas the latter goes beyond existing knowledge and generates potential scientific hypotheses. As concrete examples applied to real-world problems, this chapter looks at two applications of text data mining: gene functional annotation and genetic association discovery, both considered to have significant practical importance. © 2010, IGI Global.
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主観的トリガー言語モデルによる意見情報検索 査読あり
関和広，上原邦昭
情報処理学会論文誌：数理モデル化と応用 2009年12月
共著
担当区分：筆頭著者
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Gene Functional Annotation with Dynamic Hierarchical Classification Guided by Orthologs 査読あり
Mathieu Blondel, Kazuhiro Seki, and Kuniaki Uehara
12th International Conference on Discovery Science (DS 2009) 2009年10月
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Gene Ontology Annotation as Text Categorization: An Empirical Study 査読あり
Kazuhiro Seki and Javed Mostafa
Information Processing & Management 2009年9月
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担当区分：筆頭著者
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Discovering Implicit Associations among Critical Biological Entities 査読あり
Kazuhiro Seki and Javed Mostafa
International Journal of Data Mining and Bioinformatics 2009年5月
共著
担当区分：筆頭著者
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Adaptive Subjective Triggers for Opinionated Document Retrieval 査読あり
Kazuhiro Seki, and Kuniaki Uehara
Second ACM International Conference on Web Search and Data Mining (WSDM 2009) 2009年2月
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英語音韻を考慮した情報検索のための多様なカタカナ異表記生成 査読あり
服部弘幸，関和広，上原邦昭
情報処理学会論文誌：数理モデル化と応用 2009年2月
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Generating Diverse Katakana Variants Based on Phonemic Mapping 査読あり
Kazuhiro Seki, Hiroyuki Hattori, and Kuniaki Uehara
28th annual international ACM SIGIR conference on research and development in information retrieval (SIGIR 2008) 2008年7月
共著
担当区分：筆頭著者
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多様な遺伝子名認識と文書分類を用いたGene Ontologyアノテーション 査読あり
関和広, モスタファジャビド
電子情報通信学会論文誌 2008年4月
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担当区分：筆頭著者
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Literature-Based Discovery by an Enhanced Information Retrieval Model 査読あり
Kazuhiro Seki and Javed Mostafa
10th International Conference on Discovery Science (DS 2007) 2007年10月
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担当区分：筆頭著者
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Discovering Implicit Associations between Genes and Hereditary Diseases 査読あり
Kazuhiro Seki and Javed Mostafa
Pacific Symposium on Biocomputing (PSB) 2007年1月
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担当区分：筆頭著者
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Text Mining in Biomedicine: Discovering Implicit Associations between Genes and Disease
Kazuhiro Seki
2006年9月
単著
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An Application of Text Categorization Methods to Gene Ontology Annotation 査読あり
Kazuhiro Seki and Javed Mostafa
28th annual international ACM SIGIR conference on research and development in information retrieval (SIGIR 2005) 2005年8月
共著
担当区分：筆頭著者
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A Hybrid Approach to Protein Name Identification in Biomedical Texts 査読あり
Kazuhiro Seki and Javed Mostafa
Information Processing & Management 2005年7月
共著
担当区分：筆頭著者
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An Approach to Protein Name Extraction using Heuristics and a Dictionary 査読あり
Kazuhiro Seki and Javed Mostafa
66th American Society for Information Science and Technology Annual Conference (ASIST 2003) 2003年10月
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担当区分：筆頭著者
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A Probabilistic Model for Identifying Protein Names and their Name Boundaries 査読あり
Kazuhiro Seki and Javed Mostafa
2nd IEEE-CS Bioinformatics Conference (CSB 2003) 2003年8月
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担当区分：筆頭著者
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Protein Association Discovery in Biomedical Literature 査読あり
Kazuhiro Seki and Javed Mostafa
3rd ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL 2003) 2003年5月
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A Probabilistic Method for Analyzing Japanese Anaphora Integrating Zero Pronoun Detection and Resolution 査読あり
Kazuhiro Seki, Atsushi Fujii, and Tetsuya Ishikawa
19th International Conference on Computational Linguistics (COLING 2002) 2002年8月
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担当区分：筆頭著者
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確率モデルを用いた日本語ゼロ代名詞の照応解析 査読あり
関和広, 藤井敦, 石川徹也
自然言語処理 2002年7月
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担当区分：筆頭著者
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A Probabilistic Model for Japanese Zero Pronoun Resolution Integrating Syntactic and Semantic Features 査読あり
Kazuhiro Seki, Atsushi Fujii, and Tetsuya Ishikawa
6th Natural Language Processing Pacific Rim Symposium (NLPRS 2001) 2001年11月
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担当区分：筆頭著者