Updated on 2022/01/05

写真a

 
KOMAMIZU Takahiro
 
Organization
Mathematical and Data Science Center Associate professor
Title
Associate professor
Contact information
メールアドレス

Degree 3

  1. 博士(工学) ( 2015.3   筑波大学 ) 

  2. 修士(工学) ( 2011.3   筑波大学 ) 

  3. 学士(情報工学) ( 2009.3   筑波大学 ) 

Research Interests 5

  1. 情報検索

  2. Linked Open Data

  3. OLAP

  4. データ工学

  5. データベース

Research Areas 2

  1. Informatics / Web informatics and service informatics

  2. Informatics / Database

Research History 1

  1. University of Tsukuba   Center for Computational Sciences   Researcher

    2015.4 - 2018.1

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    Country:Japan

Education 3

  1. University of Tsukuba

    2011.4 - 2015.3

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    Country: Japan

  2. University of Tsukuba

    2009.4 - 2011.3

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    Country: Japan

  3. University of Tsukuba

    2005.4 - 2009.3

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    Country: Japan

Professional Memberships 8

  1. 電子情報通信学会   正会員

    2018.6

  2. 人工知能学会   正会員

    2018.4

  3. 言語処理学会   正会員

    2018.2

  4. the American Association for Artificial Intelligence

    2016.12 - 2017.12

  5. Association for Computing Machinery   Regular Member

    2012.5

  6. Institute of Electrical and Electronics Engineers

    2012.3

  7. 情報処理学会   正会員

    2010.6

  8. 日本データベース学会   正会員

    2008.12

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Committee Memberships 18

  1. the 9th International Workshop on Semantic Computing for Social Networks (SCSN 2021)   Program committee  

    2020.11 - 2021.1   

  2. 第18回情報学ワークショップ   プログラム委員  

    2020.9 - 2020.11   

  3. he 4th International Conference on Multimedia Information Processing and Retrieval (MIPR 2021)   Web and SNS Co-Chair  

    2020.6   

  4. the r3rdInternational Workshop on EntitY REtrieval (EYRE@CIKM2020)   Program committee  

    2020.4 - 2020.10   

  5.   PC member  

    2019.9 - 2020.2   

  6. 第17回情報学ワークショップ プログラム委員会   プログラム委員  

    2019.7 - 2019.11   

  7. 電子情報通信学会データ工学研究専門委員会   専門委員  

    2019.6   

  8.   PC member  

    2019.4 - 2019.11   

  9. 第12回データ工学と情報マネジメントに関するフォーラム (DEIM 2020) 実行委員会   幹事(Web・出版担当)  

    2019.3   

  10.   PC member  

    2018.12 - 2019.2   

  11.   PC member  

    2018.10 - 2019.7   

  12. 第16回情報学ワークショップ 実行委員会   現地実行委員  

    2018.9 - 2918.11   

  13. 言語処理学会第25回年次大会 実行委員会   実行委員  

    2018.6 - 2019.3   

  14. 第11回 Webとデータベースに関するフォーラム 実行委員会   出版・印刷担当幹事  

    2018.5 - 2018.9   

  15. 第11回データ工学と情報マネジメントに関するフォーラム (DEIM 2019) 実行委員会   Web・出版委員長  

    2018.3 - 2019.3   

  16. 第10回 Webとデータベースに関するフォーラム 実行委員会   Web担当幹事  

    2017.9   

  17. 第9回 Webとデータベースに関するフォーラム 学生奨励賞評価委員会   学生奨励賞評価委員  

    2016.9   

  18. DBSJ電子広報編集委員会   編集委員  

    2015.8   

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Awards 11

  1. 最優秀賞

    2020.11   第18回情報学ワークショップ   利用規約中の不公平文検出における不均衡データ分類に対する EasyEnsemble の利用

    近藤 匠, 駒水 孝裕, 小川 泰弘, 外山 勝彦

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    Award type:Award from Japanese society, conference, symposium, etc. 

  2. オンラインプレゼンテーション賞

    2020.3   第12回データ工学と情報マネジメントに関するフォーラム   不均衡データ分類フレームワークにおけるサンプリング比率の最適化

    植原 リサ, 駒水 孝裕, 小川 泰弘, 外山 勝彦

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    Award type:Award from Japanese society, conference, symposium, etc. 

  3. FUJITSU賞

    2019.9   第12回Webとデータベースに関するフォーラム   弱分類器の調整に基づく不均衡データ向けアンサンブル・フレームワーク

    植原 リサ, 駒水 孝裕, 小川 泰弘, 外山 勝彦

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    Award type:Award from Japanese society, conference, symposium, etc. 

  4. マイクロアド賞

    2019.9   第12回Webとデータベースに関するフォーラム   弱分類器の調整に基づく不均衡データ向けアンサンブル・フレームワーク

    植原 リサ, 駒水 孝裕, 小川 泰弘, 外山 勝彦

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    Award type:Award from Japanese society, conference, symposium, etc. 

  5. 株式会社FRONTEO賞

    2019.9   第12回Webとデータベースに関するフォーラム   弱分類器の調整に基づく不均衡データ向けアンサンブル・フレームワーク

    植原 リサ, 駒水 孝裕, 小川 泰弘, 外山 勝彦

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    Award type:Award from Japanese society, conference, symposium, etc. 

  6. JURIX 2018 Best paper award

    2018.12   Japanese Legal Term Correction using Random Forests

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    Award type:Award from international society, conference, symposium, etc.  Country:Netherlands

  7. 優秀インタラクティブ賞

    2018.3   第10回データ工学と情報マネジメントに関するフォーラム   ノードがテキスト情報を持つ動的ネットワークにおけるノードと単語の分散表現学習

    伊藤 寛祥, 駒水 孝裕, 天笠 俊之, 北川 博之

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    Award type:Award from Japanese society, conference, symposium, etc. 

  8. iiWAS 2015 Best paper award

    2015.12   the 17th International Conference on Information Integration and Web-based Applications & Services (iiWAS 2015)  

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    Award type:Award from international society, conference, symposium, etc.  Country:Belgium

  9. 情報処理学会 第73回全国大会 学生奨励賞

    2011.3   情報処理学会  

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    Award type:Award from Japanese society, conference, symposium, etc.  Country:Japan

  10. 山下記念研究賞

    2011.3   情報処理学会  

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    Award type:Award from Japanese society, conference, symposium, etc.  Country:Japan

  11. 第2回データ工学と情報マネジメントに関するフォーラム 2010 学生奨励賞

    2010.3   第2回データ工学と情報マネジメントに関するフォーラム  

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    Award type:Award from Japanese society, conference, symposium, etc.  Country:Japan

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Papers 38

  1. Random walk-based entity representation learning and re-ranking for entity search

    Komamizu Takahiro

    KNOWLEDGE AND INFORMATION SYSTEMS   Vol. 62 ( 8 ) page: 2989 - 3013   2020.8

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    Publisher:Knowledge and Information Systems  

    DOI: 10.1007/s10115-020-01445-4

    Web of Science

    Scopus

  2. ランダムフォレストを用いた法令用語の校正 Reviewed

    山腰 貴大, 小川 泰弘, 駒水 孝裕, 外山 勝彦

    人工知能学会論文誌   Vol. 35 ( 1 ) page: H-J53_1-14   2020

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    Language:Japanese   Publishing type:Research paper (scientific journal)  

    <p>We propose a method that assists legislation drafters in finding inappropriate use of Japanese legal terms and their corrections from Japanese statutory sentences. In particular, we focus on sets of similar legal terms whose usages are strictly defined in legislation drafting rules that have been established over the years. In this paper, we first define input and output of legal term correction task. We regard it as a special case of sentence completion test with multiple choices. Next, we describe a legal term correction method for Japanese statutory sentences. Our method predicts suitable legal terms using Random Forest classifiers. The classifiers in our method use adjacent words to a target legal term as input features, and are optimized in various parameters including the number of adjacent words to be used for each legal term set. We conduct an experiment using actual statutory sentences from 3,983 existing acts and cabinet orders that consist of approximately 47M words in total. As for legal term sets, we pick 27 sets from legislation drafting manuals. The experimental result shows that our method outperformed existing modern word prediction methods using neural language models and that each Random Forest classifier utilizes characteristics of its corresponding legal term set.</p>

    DOI: 10.1527/tjsai.H-J53

    Scopus

  3. Japanese mistakable legal term correction using infrequency-aware bert classifier

    Yamakoshi T.

    Transactions of the Japanese Society for Artificial Intelligence   Vol. 35 ( 4 ) page: 1 - 17   2020

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    Publisher:Transactions of the Japanese Society for Artificial Intelligence  

    DOI: 10.1527/tjsai.E-K25

    Scopus

  4. Japanese Legal Term Correction using BERT Pretrained Model

    YAMAKOSHI Takahiro, KOMAMIZU Takahiro, OGAWA Yasuhiro, TOYAMA Katsuhiko

    Proceedings of the Annual Conference of JSAI   Vol. 2020 ( 0 ) page: 4P3OS805 - 4P3OS805   2020

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    Publisher:The Japanese Society for Artificial Intelligence  

    <p>Legal documents contain legal terms that have similar meaning or pronunciation each other. Japanese legislation defines their usage on the basis of traditional customs and rules. In accordance with the definition, we need to use these legal terms properly and strictly in a statute. We are also encouraged to follow the definition in writing broad-sense legal documents, such as contracts and terms of use. To assist in writing legal documents, we propose a method that locates inappropriate legal terms in Japanese statutory sentences and suggests corrections. We solve this task with a classifier by regarding the task as a sentence completion test. Our classifier is based on a pretrained BERT model trained by using a large amount of general sentences. To raise performance, we apply three training techniques: domain adaptation, undersampling, classifier unification. Our experiments show that our classifier achieved better performance than Random Forest-based ones and language model-based ones.</p>

    DOI: 10.11517/pjsai.JSAI2020.0_4P3OS805

  5. Japanese Mistakable Legal Term Correction using Infrequency-aware BERT Classifier" Reviewed

    Takahiro Yamakoshi, Takahiro Komamizu, Yasuhiro Ogawa, Katsuhiko Toyama

    the 3rd Annual Workshop on Applications of Artificial Intelligence in the Legal Industry (LegalAI 2019)     page: 4342-4351   2019.12

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    Language:English  

  6. Japanese Mistakable Legal Term Correction using Infrequency-aware BERT Classifier

    Yamakoshi T.

    Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019     page: 4342 - 4351   2019.12

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    Publisher:Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019  

    DOI: 10.1109/BigData47090.2019.9006511

    Scopus

  7. Exploring Relevant Parts between Legal Documents using Substructure Matching Reviewed

    Takahiro Komamizu, Kazuya Fujioka, Yasuhiro Ogawa, Katsuhiko Toyama

    the Thirteenth International Workshop on Juris-informatics (JURISIN 2019)     page: 16-28   2019.11

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    Authorship:Lead author   Language:English  

  8. Analyzing Japanese Law History through Modeling Multi-versioned Entity Reviewed

    Takahiro Komamizu, Yushi Uchida, Yasuhiro Ogawa, Katsuhiko Toyama

    the 2nd International Workshop on Contextualized Knowledge Graphs (CKG 2019)     page: -   2019.10

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    Authorship:Lead author   Language:English  

  9. Thai Legal Term Correction using Random Forests with Outside-the-sentence Features Reviewed

    Takahiro Yamakoshi, Vee Satayamas, Hutchatai Chanlekha, Yasuhiro Ogawa, Takahiro Komamizu, Asanee Kawtrakul, Katsuhiko Toyama

    the 33rd Pacific Asia Conference on Language, Information and Computation (PACLIC 33)     page: 161-170   2019.9

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    Language:English  

  10. 弱分類器の調整に基づく不均衡データ向けアンサンブル・フレームワーク Reviewed

    植原 リサ, 駒水 孝裕, 小川 泰弘, 外山 勝彦

    第12回Webとデータベースに関するフォーラム     page: 81-84   2019.9

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    Language:Japanese  

  11. nagoy Team's Summarization System at the NTCIR-14 QA-Lab PoliInfo Reviewed

    Yasuhiro Ogawa, Michiaki Satou, Takahiro Komamizu, Katsuhiko Toyama

    the Fourteenth NTCIR conference (NTCIR-14) , Revised Selected Papers     page: 110-121   2019.6

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    Language:English  

  12. Detecting Communities and Correlated Attribute Clusters on Multi-Attributed Graphs

    Ito Hiroyoshi, Komamizu Takahiro, Amagasa Toshiyuki, Kitagawa Hiroyuki

    IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS   Vol. E102D ( 4 ) page: 810 - 820   2019.4

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    Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1587/transinf.2018DAP0022

    Web of Science

    Scopus

  13. Extracting Important Sentences with Random Forest for Statute Summarization

    OGAWA Yasuhiro, SATOU Michiaki, KOMAMIZU Takahiro, TOYAMA Katsuhiko

    Proceedings of the Annual Conference of JSAI   Vol. 2019 ( 0 ) page: 4E2OS7a02-4E2OS7a02   2019

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    Language:English   Publishing type:Research paper (scientific journal)  

    <p>Our purpose is to provide an automatic summarization for Japanese acts and we propose a sententence extraction method with Random Forest. While the traditional automatic summarization methods have used the information of summarizing source data, in recent years, the methods based on machine learning use the summarization results. However, in such a method, the amount of learning corpus is small, especially in Japanese text. In this research, we solve this problem by using "Outlines of Japanese Statutes," which are official summaries of statutes published by the Japanese government. Furthermore, we show that the sentence extraction method with Random Forest has higher performance rather than with decision trees or with support vector machines.</p>

    DOI: 10.11517/pjsai.JSAI2019.0_4E2OS7a02

  14. Japanese Mistakable Legal Term Correction using Infrequency-aware BERT Classifier

    Yamakoshi Takahiro, Komamizu Takahiro, Ogawa Yasuhiro, Toyama Katsuhiko

    2019 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA)     page: 4342 - 4351   2019

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  15. Japanese Legal Term Correction Using Random Forests Reviewed

    Takahiro Yamakoshi, Takahiro Komamizu, Yasuhiro Ogawa, Katsuhiko Toyama

    LEGAL KNOWLEDGE AND INFORMATION SYSTEMS (JURIX 2018)   Vol. 313   page: 161-170   2018.12

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  16. Graph Analytical Re-ranking for Entity Search

    Takahiro Komamizu

    Proceedings of the 1st International Workshop on EntitY REtrieval (EYRE 2018)     page: (to appear)   2018.10

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    Language:English  

  17. Learning Interpretable Entity Representation in Linked Data Reviewed

    Takahiro Komamizu

    Proc. the 29th International Conference on Database and Expert Systems Applications     page: 153-168   2018.9

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    Authorship:Lead author   Language:English  

  18. Community Detection and Correlated Attribute Cluster Analysis on Multi-Attributed Graphs Reviewed

    Hiroyoshi Ito, Takahiro Komamizu, Toshiyuki Amagasa, Hiroyuki Kitagawa

    Proc. the 2nd International workshop on Data Analytics solutions for Real-LIfe APplications (DARLI-AP 2018) co-located with the 21st International Conference on Extending Database Technology (EDBT 2018)     2018.3

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    Language:English  

    DOI: 2-9

  19. Network-Word Embedding for Dynamic Text Attributed Networks Reviewed

    Hiroyoshi Ito, Takahiro Komamizu, Toshiyuki Amagasa, Hiroyuki Kitagawa

    Proc. the 6th International Workshop on Semantic Computing for Social Networks and Organization Sciences (SCSN 2018) co-located with the 12th IEEE International Conference on Semantic Computing (ICSC 2018)     2018.1

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    Language:English  

    DOI: 334-339

  20. Analytical toolbox for smart city applications: Garbage collection log use case Reviewed

    Takahiro Komamizu, Jin Nakazawa, Toshiyuki Amagasa, Hiroyuki Kitagawa, Hideyuki Tokuda

    Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017   Vol. 2018-   page: 4105 - 4110   2018.1

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:Institute of Electrical and Electronics Engineers Inc.  

    Analyzing and feeding back the results on real-world services are important missions in the Big Data era to realize smart city. However, analyzing real-world data is still challenging because of dirtiness of data and large variety of analytic requirements. To cope with the challenges, this paper proposes and develops an analytical toolbox for smart city applications. The analytical toolbox consists of three phases: preparation, analysis, and visualization. The preparation phase deals with the dirtiness of the data by including fundamental data cleansing techniques and data integration techniques. The analysis phase is responsible for ETL (extract, transform and load) process and analytical query processing from the next phase. The visualization phase deals with analytical requirements from users and visualization of analytical results. This paper showcases a real-world use case of the proposed analytical toolbox. The use case is now open in public with help of Fujisawa city, Japan, and this fact indicates that the proposed analytical toolbox is feasible for real-world data analysis and feeding back to citizens.

    DOI: 10.1109/BigData.2017.8258429

    Scopus

  21. Implicit order join: Joining log data with property data by discovering implicit order-oriented keys with human assistance Reviewed

    Takahiro Komamizu, Toshiyuki Amagasa, Hiroyuki Kitagawa

    Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017   Vol. 2018-   page: 4400 - 4406   2018.1

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:Institute of Electrical and Electronics Engineers Inc.  

    Data integration is still laboursome task when integrating data are not consistently managed. Such inconsistency can happen easily in real-world situations, such as properties of objects are managed by a central organization and trajectories (or logs) of the objects are recorded by other peripheral organizations. This paper deals with a case of missing ordering information. Integrating property data and log data without ordering information causes duplicated results. In order to solve this problem, this paper proposes a join algorithm, called implicit order join, which discovers implicit ordering information from both property data and log data with help of partial true integrated results from human assistance. With the discovered ordering information, the implicit order join enables to integrate the property data and log data. In order to discover the implicit ordering information, ordering correlation between attribute sequences of property data and log data should be found from comprehensive examination of possible attribute sequence pairs. The potential number of sequence pairs is as high as factorial order of the number of attributes. Therefore, this paper develops a heuristic approach to prune unnecessary examinations based on ordering dependency between attribute sequences. Experimental evaluation in this paper indicates that implicit order join can reduce 77% labouring tasks for integration and the pruning method reduces the number of attribute sequences in orders of magnitude.

    DOI: 10.1109/BigData.2017.8258474

    Scopus

  22. CROISSANT: Centralized Relational Interface for Web-scale SPARQL Endpoints Reviewed

    Takahiro Komamizu, Toshiyuki Amagasa, Hiroyuki Kitagawa

    Proc. the 19th International Conference on Information Integration and Web-based Applications & Services (iiWAS2017)     2017.12

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    Authorship:Lead author   Language:English  

    DOI: 284-288

  23. SOLA: Stream OLAP-based Analytical Framework for Roadway Maintenance Reviewed

    Takahiro Komamizu, Toshiyuki Amagasa, Salman Ahmed Shaikh, Hiroaki Shiokawa, Hiroyuki Kitagawa

    Proc. the 9th International Conference on Management of Digital EcoSystems (MEDES 2017)     2017.11

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    Authorship:Lead author   Language:English  

    DOI: 35-42

  24. GitHubとStack Overflowの開発者の活動記録を併用したリポジトリ推薦 Reviewed

    永野 真知, 早瀬 康裕, 駒水 孝裕, 北川 博之

    ソフトウェアエンジニアリングシンポジウム 2017論文集     2017.8

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    Language:Japanese  

    DOI: 138-145

  25. FORK: Feedback-Aware ObjectRank-Based Keyword Search over Linked Data Reviewed

    Takahiro Komamizu, Sayami Okumura, Toshiyuki Amagasa, Hiroyuki Kitagawa

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   Vol. 10648   page: 58 - 70   2017

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:Springer Verlag  

    Ranking quality for keyword search over Linked Data (LD) is crucial when users look for entities from LD, since datasets in LD have complicated structures as well as much contents. This paper proposes a keyword search method, FORK, which ranks entities in LD by ObjectRank, a well-known link-structure analysis algorithm that can deal with different types of nodes and edges. The first attempt of applying ObjectRank to LD search reveals that ObjectRank with inappropriate settings gives worse ranking results than PageRank which is equivalent to ObjectRank with all the same authority transfer weights. Therefore, deriving appropriate authority transfer weights is the most important issue for encouraging ObjectRank in LD search. FORK involves a relevance feedback algorithm to modify the authority transfer weights according with users’ relevance judgements for ranking results. The experimental evaluation of ranking qualities using an entity search benchmark showcases the effectiveness of FORK, and it proves ObjectRank is more feasible raking method for LD search than PageRank and other comparative baselines including information retrieval techniques and graph analytic methods.

    DOI: 10.1007/978-3-319-70145-5_5

    Scopus

  26. Exploring identical users on GitHub and stack overflow Reviewed

    Takahiro Komamizu, Yasuhiro Hayase, Toshiyuki Amagasa, Hiroyuki Kitagawa

    Proceedings of the International Conference on Software Engineering and Knowledge Engineering, SEKE     page: 584 - 589   2017

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:Knowledge Systems Institute Graduate School  

    Analyzing behaviours of developers in different platforms (in particular, GitHub and Stack Overflow in this paper) can reveal interesting facts related to development activities. There are only few datasets for analysing crossplatform user behaviours, especially across GitHub and Stack Overflow. Users on GitHub and Stack Overflow are identifiable by equivalences of email addresses. In order to increase the number of identifiable users on these datasets, this paper retrieves potentially identifiable users between GitHub and Stack Overflow not relying only on email addresses. This paper employs a classification-based link prediction, which design the user identification problem as a link prediction problem on the bipartite graph consisting of users of GitHub and those of Stack Overflow. With the identification method, this paper generates a probabilistic dataset containing pairs of users with probabilities (or confidences). This paper, as well, publishes the identification tool in order to enable further data generation on appearing datasets of GitHub, Stack Overflow and others. The generated dataset and tool are highly helpful to accelerate researches on mining software repositories.

    DOI: 10.18293/SEKE2017-109

    Scopus

  27. Towards Real-time Analysis of Smart City Data: A Case Study on City Facility Utilizations Reviewed

    Takahiro Komamizu, Toshiyuki Amagasa, Salman Ahmed Shaikh, Hiroaki Shiokawa, Hiroyuki Kitagawa

    Proc. the 14th IEEE International Conference on Smart City (SmartCity 2016)     page: 1357-1364   2016.12

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    Authorship:Lead author   Language:English  

    DOI: 10.1109/HPCC-SmartCity-DSS.2016.0192

  28. Interleaving Clustering of Classes and Properties for Disambiguating Linked Data Reviewed

    Takahiro Komamizu, Toshiyuki Amagasa, Hiroyuki Kitagawa

    Proc. the 18th International Conference on Asia-Pacific Digital Libraries (ICADL 2016)     2016.12

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    Authorship:Lead author   Language:English  

    DOI: 251-256

  29. Visual Spatial-OLAP for Vehicle Recorder Data on Micro-sized Electric Vehicles Reviewed

    Takahiro Komamizu, Toshiyuki Amagasa, Hiroyuki Kitagawa

    Proc. the 20th International Database Engineering & Applications Symposium (IDEAS 2016)     page: 358-363   2016.7

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    Authorship:Lead author   Language:English  

    DOI: 10.1145/2938503.2938532

  30. H-SPOOL: A SPARQL-based ETL Framework for OLAP over Linked Data with Dimension Hierarchy Extraction Invited Reviewed

    Takahiro Komamizu, Toshiyuki Amagasa, Hiroyuki Kitagawa

      Vol. 12 ( 3 ) page: 359-378   2016.6

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    Authorship:Lead author   Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1108/IJWIS-03-2016-0014

  31. SPOOL: A SPARQL-based ETL Framework for OLAP over Linked Data Reviewed

    Takahiro Komamizu, Toshiyuki Amagasa, Hiroyuki Kitagawa

    Proc. the 17th International Conference on Information Integration and Web-based Applications & Services (iiWAS 2015)   ( 49 ) page: 1-10   2015.12

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    Authorship:Lead author   Language:English  

    DOI: 10.1145/2837185.2837230

  32. Facet-value Extraction Scheme from Textual Contents in XML Data Invited Reviewed

    Takahiro Komamizu, Toshiyuki Amagasa, Hiroyuki Kitagawa

      Vol. 11 ( 3 ) page: 270-290   2015.6

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    Authorship:Lead author   Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1108/IJWIS-04-2015-0012

  33. Extracting Facets from Textual Contents for Faceted Search over XML Data Reviewed

    Takahiro Komamizu, Toshiyuki Amagasa, Hiroyuki Kitagawa

    Proc. the 16th International Conference on Information Integration and Web-based Applications & Services (iiWAS 2014)     page: 420-429   2014.12

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    Authorship:Lead author   Language:English  

    DOI: 10.1145/2684200.2684294

  34. Frequent-Pattern based Facet Extraction from Graph Data Reviewed

    Takahiro Komamizu, Toshiyuki Amagasa, Hiroyuki Kitagawa

    Proc. the 17th International Conference on Network-Based Information Systems (NBiS 2014)     page: 318-323   2014.9

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    Authorship:Lead author   Language:English  

    DOI: 10.1109/NBiS.2014.77

  35. A Scheme of Automated Object and Facet Extraction for Faceted Search over XML Data Reviewed

    Takahiro Komamizu, Toshiyuki Amagasa, Hiroyuki Kitagawa

    Proc. the 18th International Database Engineering & Applications Symposium (IDEAS 2014)     page: 338-341   2014.7

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    Authorship:Lead author   Language:English  

    DOI: 10.1145/2628194.2628241

  36. A Scheme of Fragment-Based Faceted Image Search Reviewed

    Takahiro Komamizu, Mariko Kamie, Kazuhiro Fukui, Toshiyuki Amagasa, Hiroyuki Kitagawa

    Proc. the 23rd International Conference on Database and Expert Systems Applications (DEXA 2012)     page: 450-457   2012.9

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    Authorship:Lead author   Language:English  

    DOI: 10.1007/978-3-642-32597-7_40

  37. Faceted Navigation Framework for XML Data Invited Reviewed

    Takahiro Komamizu, Toshiyuki Amagasa, Hiroyuki Kitagawa

      Vol. 8 ( 4 ) page: 348-370   2012.8

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    Authorship:Lead author   Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1108/17440081211282865

  38. A Framework of Faceted Navigation for XML Data Reviewed

    Takahiro Komamizu, Toshiyuki Amagasa, Hiroyuki Kitagawa

    Proc. the 13th International Conference on Information Integration and Web-based Applications & Services (iiWAS 2011)     page: 28-35   2011.12

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    Authorship:Lead author   Language:English  

    DOI: 10.1145/2095536.2095544

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Presentations 32

  1. 法令沿革オントロジーの設計

    内田 勇志, 駒水 孝裕, 小川 泰弘, 外山 勝彦

    第47回人工知能学会セマンティックウェブとオントロジー(SWO)研究会 

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    Event date: 2019.3

    Language:Japanese   Presentation type:Oral presentation (general)  

    Country:Japan  

  2. グラフ構造を利用したエンティティ検索

    駒水 孝裕

    第11回データ工学と情報マネジメントに関するフォーラム 

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    Event date: 2019.3

    Language:Japanese   Presentation type:Oral presentation (general)  

    Country:Japan  

  3. 部分構造を用いた類似例規の検索

    藤岡 和弥, 駒水 孝裕, 小川 泰弘, 外山 勝彦

    第11回データ工学と情報マネジメントに関するフォーラム 

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    Event date: 2019.3

    Language:Japanese   Presentation type:Oral presentation (general)  

    Country:Japan  

  4. nagoy Team’s Summarization System at the NTCIR-14 QA Lab-PoliInfo

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    Event date: 2019

    Language:English   Presentation type:Oral presentation (general)  

    DOI: 10.1007/978-3-030-36805-0_9

    Scopus

  5. 並列構造の分割による法令文の読解性向上

    青山 恵子, 駒水 孝裕, 小川 泰弘, 外山 勝彦

    平成30年度 電気・電子・情報関係学会 東海支部連合大会 

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    Event date: 2018.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Country:Japan  

  6. ランダムフォレストによる法令用語の校正

    山腰 貴大, 駒水 孝裕, 小川 泰弘, 外山 勝彦

    平成30年度 電気・電子・情報関係学会 東海支部連合大会 

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    Event date: 2018.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Country:Japan  

  7. ニューラルモデルと翻訳メモリを併用した機械翻訳

    重野 泰和, 駒水 孝裕, 小川 泰弘, 外山 勝彦

    平成30年度 電気・電子・情報関係学会 東海支部連合大会 

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    Event date: 2018.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Country:Japan  

  8. 分類器を用いた法令要約に利用する法令文の自動抽出

    佐藤 充晃, 駒水 孝裕, 小川 泰弘, 外山 勝彦

    平成30年度 電気・電子・情報関係学会 東海支部連合大会 

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    Event date: 2018.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Country:Japan  

  9. 単語の分散表現を用いた法令用語間の関係の獲得

    植原 リサ, 駒水 孝裕, 小川 泰弘, 外山 勝彦

    平成30年度 電気・電子・情報関係学会 東海支部連合大会 

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    Event date: 2018.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Country:Japan  

  10. Zipf の法則は例規文の出現数においても成立する

    藤岡 和弥, 駒水 孝裕, 小川 泰弘, 外山 勝彦

    平成30年度 電気・電子・情報関係学会 東海支部連合大会 

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    Event date: 2018.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Country:Japan  

  11. グラフ集約に基づくRDFデータに対するOLAP分析

    仁木 美来, 天笠 俊之, 駒水 孝裕, 北川 博之

    情報処理学会第80回全国大会 

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    Event date: 2018.3

    Language:Japanese   Presentation type:Oral presentation (general)  

    Country:Japan  

  12. ノードがテキスト情報を持つ動的ネットワークにおけるノードと単語の分散表現学習

    伊藤 寛祥, 駒水 孝裕, 天笠 俊之, 北川 博之

    第10回データ工学と情報マネジメントに関するフォーラム 

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    Event date: 2018.3

    Language:Japanese   Presentation type:Oral presentation (general)  

    Country:Japan  

  13. ゴミ減量G1グランプリ Invited

    駒水 孝裕

    第1回 地域IoTと情報力シンポジウム 

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    Event date: 2017.4

    Language:Japanese   Presentation type:Poster presentation  

    Country:Japan  

  14. GitHubとStack Overflowにおけるユーザ行動の統一的な分析

    永野 真知, 早瀬 康裕, 駒水 孝裕, 北川 博之

    情報処理学会第79回全国大会 

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    Event date: 2017.3

    Language:Japanese   Presentation type:Oral presentation (general)  

    Country:Japan  

  15. ノードが複数の属性を持つグラフにおけるコミュニティ検出

    伊藤 寛祥, 駒水 孝裕, 天笠 俊之, 北川 博之

    第9回データ工学と情報マネジメントに関するフォーラム 

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    Event date: 2017.3

    Language:Japanese   Presentation type:Oral presentation (general)  

    Country:Japan  

  16. XMLデータに対するファセット検索のためのファセット抽出の自動化

    駒水 孝裕, 天笠 俊之, 北川 博之

    第13回情報科学技術フォーラム 

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    Event date: 2014.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Country:Japan  

  17. グラフデータに対するファセット探索のための頻出パターンを利用したオブジェクト抽出手法

    駒水 孝裕, 天笠 俊之, 北川 博之

    第4回データ工学と情報マネジメントに関するフォーラム 

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    Event date: 2012.3

    Language:Japanese   Presentation type:Oral presentation (general)  

    Country:Japan  

  18. データ工学分野における技術と研究 Invited

    駒水 孝裕

    科目「ICT活用」 

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    Event date: 2012.2

    Language:Japanese   Presentation type:Public lecture, seminar, tutorial, course, or other speech  

    Country:Japan  

  19. ソフトウェア部品検索に適したファセット探索の一考察

    駒水 孝裕, 早瀬 康裕, 北川 博之

    ソフトウェアサイエンス研究会 

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    Event date: 2011.10

    Language:Japanese   Presentation type:Oral presentation (general)  

    Country:Japan  

  20. FACTUS: Faceted Twitter User Search Using Twitter Lists International conference

    Takahiro Komamizu, Yuto Yamaguchi, Toshiyuki Amagasa, Hiroyuki Kitagawa

    Proc. the 12th International Conference on Web Information System Engineering (WISE 2011) 

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    Event date: 2011.10

    Language:English   Presentation type:Poster presentation  

    Country:Australia  

  21. XMLデータに対するファセット検索のユーザビリティ評価

    駒水 孝裕, 天笠 俊之, 北川 博之

    情報処理学会第73回全国大会 

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    Event date: 2011.3

    Language:Japanese   Presentation type:Oral presentation (general)  

    Country:Japan  

  22. キーワード検索が可能なXMLデータに対するファセット探索

    駒水 孝裕, 天笠 俊之, 北川 博之

    第3回データ工学と情報マネジメントに関するフォーラム 

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    Event date: 2011.2 - 2011.3

    Language:Japanese   Presentation type:Oral presentation (general)  

    Country:Japan  

  23. 異種XMLデータに対するファセット検索システムの性能評価

    駒水 孝裕, 天笠 俊之, 北川 博之

    情報処理学会第72回全国大会 

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    Event date: 2010.3

    Language:Japanese   Presentation type:Oral presentation (general)  

    Country:Japan  

  24. 異種XMLデータに対するファセット検索における多様な検索

    駒水 孝裕, 天笠 俊之, 北川 博之

    第2回データ工学と情報マネジメントに関するフォーラム 

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    Event date: 2010.2 - 2010.3

    Language:Japanese   Presentation type:Oral presentation (general)  

    Country:Japan  

  25. 異種XMLデータに対するファセット検索手法の提案

    駒水 孝裕, 天笠 俊之, 北川 博之

    デジタルドキュメント研究会 

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    Event date: 2009.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Country:Japan  

  26. XMLデータに対するファセットナビゲーションのためのフレームワークFoXの提案

    駒水 孝裕, 天笠 俊之, 北川 博之

    第1回データ工学と情報マネジメントに関するフォーラム 

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    Event date: 2009.3

    Language:Japanese   Presentation type:Oral presentation (general)  

    Country:Japan  

  27. Exploring Relevant Parts Between Legal Documents Using Substructure Matching

    Komamizu T.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)  2020  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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  28. Analyzing Japanese law history through modeling multi-versioned entity

    Komamizu T.

    CEUR Workshop Proceedings  2019  CEUR Workshop Proceedings

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  29. Learning Interpretable Entity Representation in Linked Data

    Komamizu T.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)  2018  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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  30. Thai legal term correction using random forests with outside-the-sentence features

    Yamakoshi T.

    Proceedings of the 33rd Pacific Asia Conference on Language, Information and Computation, PACLIC 2019  2019  Proceedings of the 33rd Pacific Asia Conference on Language, Information and Computation, PACLIC 2019

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  31. SPARQL with XQuery-based filtering

    Komamizu T.

    CEUR Workshop Proceedings  2020  CEUR Workshop Proceedings

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  32. Muensemble: Multi-ratio undersampling-based ensemble framework for imbalanced data

    Komamizu T.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)  2020  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Research Project for Joint Research, Competitive Funding, etc. 1

  1. 公益財団法人 人工知能研究振興財団 研究助成

    2019.1 - 2020.9

KAKENHI (Grants-in-Aid for Scientific Research) 2

  1. 異種オープンデータ活用のためのデータ統合・管理基盤の研究開発

    Grant number:21H03555  2021.4 - 2025.3

    駒水 孝裕

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    Authorship:Principal investigator 

    Grant amount:\17160000 ( Direct Cost: \13200000 、 Indirect Cost:\3960000 )

  2. 大規模データ分析のための多視点分析管理システムの研究開発

    2018.4 - 2021.3

    科学研究費補助金 

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    Authorship:Principal investigator 

 

Teaching Experience (On-campus) 3

  1. 情報工学実験

    2018

  2. 数理科学基礎演習

    2018

  3. データ処理ツール演習

    2018