Papers - Kudo Yasuo

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  1. Relative pre-reducts for computing the relative reducts of large data sets

    Hajime Okawa, Yasuo Kudo, and Tetsuya Murai，International Journal of Approximate Reasoning，vol.187，Article Number:109544，2025.08

  2. Vector-based rough sets

    Hajime Okawa, Yasuo Kudo, Tetsuya MUrai，Information Sciences，vol.717，Article Number:122331，2025.05

  3. 可変精度ラフ集合におけるβ-縮約の改良とその計算

    中濱 慶紀, 大川 創, 工藤 康生, 村井 哲也，知能と情報（日本知能情報ファジィ学会誌），vol.37，(1)，(p.126 ～ 136)，2025.02

  4. ヒト型化オセロAIのための思考とカーソル移動の時間的制御

    服部峻, 黒野真澄, 吉田裕太, 高原まどか, 工藤康生，情報処理学会論文誌　データベース，vol.16，(2)，(p.16 ～ 33)，2023.04

  5. 個性除去を用いたツンデレキャラ型化チャットAIの対話応答制御

    服部峻, 森康汰, 高原まどか, 工藤康生，情報処理学会論文誌　データベース，vol.16，(2)，(p.34 ～ 49)，2023.04

  6. 決定表の対象の更新に伴う相対縮約の再計算方法の改良

    橋本 祥奈, 大川 創, 工藤 康生, 村井 哲也，知能と情報（日本知能情報ファジィ学会誌），vol.35，(1)，(p.624 ～ 632)，2023.02

  7. Educational Recommendation System Utilizing Learning Styles: A Systematic Literature Review

    Vivat Thongchotchat, Yasuo Kudo, Yoshifumi Okada, and Kazuhiko Sato，IEEE Access，vol.11，(p.8988 ～ 8999)，2023.01

  8. Context-Enhanced Probabilistic Diffusion for Urban Point-of-Interest Recommendation

    Zhipeng Zhang, Mianxiong Dong, Kaoru Ota, Yao Zhang, and Yasuo Kudo，IEEE Transactions on Services Computing，vol.15，(6)，(p.3156 ～ 3169)，Article Number:22385859，2022.12

  9. ラフ集合における擬一般化動的縮約の抽出手法の改良

    工藤　康生，高橋　智，村井　哲也，知能と情報（日本知能情報ファジィ学会誌），vol.32，(4)，(p.759 ～ 767)，2020.08

  10. Improved covering-based collaborative filtering for new users' personalized recommendations

    Zhipeng Zhang, Yasuo Kudo, Tetsuya Murai, and Yonggong Ren，Knowledge and Information Systems，2020.03

  11. Alleviating New User Cold-Start in User-Based Collaborative Filtering via Bipartite Network

    Zhipeng Zhang, Mianxiong Dong, Kaoru Ota, and Yasuo Kudo，IEEE Transactions on Computational Social Systems，vol.7，(3)，(p.672 ～ 685)，2020.03

  12. Enhancing Recommendation Accuracy of Item-Based Collaborative Filtering via Item-Variance Weighting

    Zhi-Peng Zhang, Yasuo Kudo, Tetsuya Murai, and Yong-Gong Ren，Applied Sciences-Basel，vol.9，(9)，Article Number:1928，2019.05

  13. Addressing Complete New Item Cold-Start Recommendation: A Niche Item-Based Collaborative Filtering via Interrelationship Mining

    Zhi-Peng Zhang, Yasuo Kudo, Tetsuya Murai, and Yong-Gong Ren，Applied Sciences-Basel，vol.9，(9)，Article Number:1894，2019.05

  14. 関係性マイニングと協調フィルタリングを用いた情報推薦手法

    山脇 淳一, 工藤 康生, 村井 哲也， 日本感性工学会論文誌，vol.17，(4)，(p.481 ～ 488)，2018.08

  15. Partial and paraconsistent approaches to future contingents in tense logic

    Seiki Akama, Tetsuya Murai, and Yasuo Kudo，Synthesis，vol.193，(11)，(p. 3639 ～ 3649)，2016.11

  16. Neighbor selection for user-based collaborative filtering using covering-based rough sets

    Zhipeng Zhang, Yasuo Kudo, and Tetsuya Murai，Annals of Operations Research，(p.1 ～ 16)，2016.11

  17. Rough-set-based Interrelationship Mining for Incomplete Decision Tables

    Yasuo Kudo and Tetsuya Murai，Journal of Advanced Computational Intelligence and Intelligent Informatics，vol.20，(5)，(p.712 ～ 720)，2016.09

  18. Fuzzy Multisets in Granular Hierarchical Structures Generated from Free Monoids

    Tetsuya Murai, Sadaaki Miyamoto, Masahiro Inuiguchi, Yasuo Kudo, and Seiki Akama，Journal of Advanced Computational Intelligence and Intelligent Infomatics，vol.19，(1)，(p.43 ～ 50)，2015.01

  19. Variable Neighborhood Model for Agent Control Introducing Accessibility Relations Between Agents with Linear Temporal Logic

    Seiki Ubukata, Tetsuya Murai, Yasuo Kudo, and Seiki Akama，Journal of Advanced Computational Intelligence and Intelligent Infomatics，vol.18，(6)，(p.937 ～ 945)，2014.11

  20. A Formulation of Artificial Kansei Systems Based on Multi-agent Spaces Generated by Variable Neighborhood Models

    Seiki Ubukata, Yasuo Kudo, and Tetsuya Murai，International Journal of Affective Engineering，vol.13，(1)，(p.81 ～ 87)，2014.01

  21. Epistemic Logic Founded on Nonignorance

    Seiki Akama, Tetsuya Murai and Yasuo Kudo，International Journal of Intelligent Systems，vol.28，(9)，(p.883 ～ 891)，2013.09

  22. 主体的学習を促す「与えない」演習の実践

    佐藤和彦，倉重健太郎，寺本渉，工藤康生，佐賀聡人，工学教育，vol.61，(3)，(p.56 ～ 61)，2013.06

  23. A Parallel Computation Method for Heuristic Attribute Reduction Using Reduced Decision Tables

    Yasuo Kudo and Tetsuya Murai，Journal of Advanced Computational Intelligence and Intelligent Informatics，vol.17，(3)，(p.371 ～ 376)，2013.05

  24. A Revised Approach to Solving the Symbolic Value Partition Problem from a Viewpoint of Roughness of Partitions

    Yasuo Kudo，Int. J. Reasoning-based Intelligent Systems，vol.4，(5)，(p.129 ～ 139)，2012.11

  25. Study on Feature Extraction Method for Product Design --- Proposal for Method of Inferring Decisoin Classes by Variable Precision Rough Sets Models and Principle Componet Analysis

    関口彰・井上勝雄・酒井祐輔・工藤康生，Bulletin of Japanese Society for the Science of Design，vol.58，(3)，(p.59 ～ 68)，2011.12

  26. A heuristic method for discovering biomarker candidates based on rough set theory

    Yasuo Kudo and Yoshifumi Okada，Bioinformation，vol.6，(5)，(p.200 ～ 203)，2011.06

  27. A sequential pattern mining algorithm using rough set theory

    Ken Kaneiwa and Yasuo Kudo，International Journal of Approximate Reasoning，vol.52，(p.881 ～ )，2011.04

  28. Autonomous agent control based on variable neighbourhoods

    Seiki Ubukata, Yasuo Kudo, and Tetsuya Murai，International Journal of Reasoning-based Intelligent Systems，vol.3，(1)，(p.8 ～ 13)，2011.01

  29. Heuristic Algorithm for Attribute Reduction Based on Classification Ability by Condition Attributes

    Yasuo Kudo and Tetsuya Murai，Journal of Advanced Computational Intelligence and Intelligent Infomatics，vol.15，(1)，(p.102 ～ 109)，2011.01

  30. An Evaluation Method of Relative Reducts Based on Roughness of Partitions

    Yasuo Kudo and Tetsuya Murai，International Journal of Cognitive Informatics and Natural intelligence，vol.4，(2)，(p.50 ～ 62)，2010.06

  31. Network Inversion for the Cocktail-Data Quantification using Distance Mapping Learning Networks

    奥谷 勝行, 塩谷 浩之, 工藤 康生, 沖井 廣宣，Journal of Japan Society of Kansei Engineering，vol.9，(2)，(p.431 ～ 437)，2010.02

  32. An Application of Rough Set Analysis to a Psycho-Physiological Study - Assessing the Relation Between Psychological Scale and Immunological Biomarker

    Shusaku Nomura and Yasuo Kudo，Journal of Advanced Computational Intelligence and Intelligent Informatics，vol.13，(4)，(p.352 ～ 359)，2009.07

  33. A Granularity-Based Framework of Deduction, Induction and Abduction

    Yasuo Kudo, Tetsuya Murai and Seiki Akama，International Journal of Approximate Reasoning，vol.50，(8)，(p.1215 ～ 1226)，2009.06

  34. A Modal Characterization of Visibility and Focus in Granular Reasoning

    Yasuo Kudo and Tetsuya Murai，Journalof Advanced Computational Intelligence and Intelligent Infomatics，vol.13，(3)，(p.297 ～ 303)，2009.05

  35. Missing Value Semantics and Absent Value Semantics for Incomplete Information in Object-Oriented Rough Set Models

    Yasuo Kudo and Tetsuya Murai，Granular Computing: At the Junction ofRough Sets and Fuzzy Sets，(p.3 ～ 21)，2008

  36. A Role of Granularity and Background Knowledge in Reasoning Processes

    Tetsuya Murai, Yasuo Kudo and Seiki Akama，Kansei Engineering International，vol.6，(3)，(p.41 ～ 46)，2006.11

  37. A Simple Recommendation System Based on Rough Set Theory

    Yasuo Kudo, Shohei Amano, Takahiro Seino and Tetsuya Murai，Kansei Engineering International，vol.6，(3)，(p.19 ～ 24)，2006.11

  38. A Theoretical Formulation of Object--Oriented Rough Set Models

    Yasuo Kudo and Tetsuya Murai，Journal of Advanced Computational Intelligence and Intelligent Informatics，vol.10，(5)，(p.612 ～ 620)，2006.09

  39. A Family of Polymodal Systems and Its Application to Generalized Possibility Measures and Multi-Rough Sets

    Sadaaki Miyamoto, Tetsuya Murai and Yasuo Kudo，Journal of AdvancedComputational Intelligence and Intelligent Informatics，vol.10，(5)，(p.625 ～ 632)，2006.09

  40. Image Retrieval of Large Intestine Images Using Feature Selection Agents

    沖井広宣・工藤康生・寺島賢紀，パーソナルコンピュータユーザ利用技術協会論文誌，vol.16，(3)，(p.53 ～ 60)，2006.03

  41. Detection of Facial Parts Regions Without Using Tempate Matching

    沖井広宣・工藤康生・寺島賢紀，パーソナルコンピュータユーザ利用技術協会論文誌，vol.16，(2)，(p.101 ～ 108)，2005.10

  42. A Logical Representation of Belief Update Based on Modal Logics of Ordered Arrows

    工藤康生・村井哲也・伊達惇，Journal of Japanese Society for Artificial Intelligence，vol.15，(2)，(p.339 ～ 347)，2000.03

  43. On a formulation of belief update in possibility theory

    工藤康生・村井哲也・伊達惇，Journal of Japan Society for Fuzzy Theory and Systems，vol.11，(4)，(p.640 ～ 649)，1999.08

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