Updated on 2025/04/11

写真a

 
Honda Katsuhiro
 
Organization
Graduate School of Informatics Department of Core Informatics Professor
School of Engineering Department of Information Science
Title
Professor
Affiliation
Institute of Informatics
Affiliation campus
Nakamozu Campus

Position

  • Graduate School of Informatics Department of Core Informatics 

    Professor  2022.04 - Now

  • School of Engineering Department of Information Science 

    Professor  2022.04 - Now

Degree

  • 博士(工学) ( Others )

  • 修士(工学) ( Others )

Research Areas

  • Informatics / Soft computing

  • Informatics / Kansei informatics  / 感性情報学・ソフトコンピューティング

  • Informatics / Intelligent informatics

  • Informatics / Statistical science

Research Interests

  • Fuzzy Clustering

  • Fuzzy Data Analysis

Research subject summary

  • k匿名化によるプライバシー保護データ解析

  • クラスタリングに基づく協調フィルタリング

  • 大規模データベースからの知識発見

  • データ解析を目的としたクラスタリング法

Research Career

  • Intelligent Data Analysis

    Fuzzy clustering, Multi-variate data analysis, Soft computing, Sensitivity Informatics 

Professional Memberships

  • システム制御情報学会

    2001.04 - Now

  • IEEE

    2000.04 - Now

  • 日本知能情報ファジィ学会

    1999.04 - Now

  • 日本経営工学会

    1997.04 - Now

Committee Memberships (off-campus)

  • 理事(大会デザイン)   日本知能情報ファジィ学会  

    2021.06 - 2023.06 

  • 第17期理事   日本知能情報ファジィ協会  

    2021.04 - 2022.03 

  • 理事(事業委員長)   日本知能情報ファジィ学会  

    2017.06 - 2019.06 

  • 理事(財務)   システム制御情報学会  

    2017.05 - 2019.05 

Awards

  • Best Paper Award 2022

    K. Honda, I. Hayashi, S. Ubukata, A. Notsu

    2022.09   Journal of Advanced Computational Intelligence and Intelligent Informatics   Three-Mode Fuzzy Co-Clustering Based on Probabilistic Concept and Comparison with FCM-Type Algorithms

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    Country:Japan

  • 2021 SICE Annual Conference International Award

    2021.09   Society of Instrument and Control Engineers  

  • Excellent Paper Award

    2020.09   International Symposium on Community-centric Systems 2020  

  • Best Paper Award

    2016.08   Joint 8th International Conference on Soft Computing and Intelligent Systems and 17th International Symposium on Advanced Intelligent Systems  

  • 貢献賞

    2013.09   日本知能情報ファジィ学会  

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    Country:Japan

  • 論文賞

    2012.09   日本知能情報ファジィ学会  

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    Country:Japan

  • 論文賞

    2011.09   日本知能情報ファジィ学会  

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    Country:Japan

  • 著述賞

    2010.09   日本知能情報ファジィ学会  

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    Country:Japan

  • 奨励賞

    2005.09   日本知能情報ファジィ学会  

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    Country:Japan

  • 論文賞

    2002.08   日本ファジィ学会  

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    Country:Japan

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Papers

  • A Comparative Study on Effects of Some Exclusive Conditions in Fuzzy Co-Clustering for Collaborative Filtering Reviewed OA

    14   14589 - 14594   2023.11

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    Authorship:Lead author, Corresponding author   Kind of work:Joint Work   International / domestic magazine:International journal  

    DOI: 10.1007/s12652-018-0789-0

  • Addition of Out-of-Population Search in JADE Reviewed

    MIYAHIRA Yuichi, IGUCHI Makishi, NOTSU Akira, HONDA Katsuhiro

    Journal of Japan Society for Fuzzy Theory and Intelligent Informatics   35 ( 1 )   532 - 537   2023.02( ISSN:13477986 ( eISSN:18817203

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    Publishing type:Research paper (scientific journal)  

    <p>JADE is an optimization algorithm that uses probability distributions to adaptively select parameters. However, it does not take into account the search for regions outside the solution population, so it can be improved by adding an efficient out-of-population search such as the Nelder-Mead method. In this study, a simple method with a small number of parameters to add out-of-population search was considered while keeping the search speed as high as possible, and its effectiveness was confirmed through numerical experiments.</p>

    DOI: 10.3156/jsoft.35.1_532

  • Robust Fuzzy Factorization Machine with Noise Clustering-based Membership Function Estimation Reviewed

    K. Honda, K. Hoshii, S. Ubukata, A. Notsu

    Soft Computing Letters 雑誌   3 ( 100024 )   2021.12

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    Kind of work:Joint Work  

  • Three-mode Fuzzy Co-clustering Based on Probabilistic Concept and Comparison with FCM-type algorithms Reviewed

    K. Honda, I. Hayashi, S. Ubukata, A. Notsu

    Journal of Advanced Computational Intelligence and Intelligent Informatics 雑誌   25 ( 4 )   478 - 488   2021.07

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    Kind of work:Joint Work  

  • Linear Fuzzy Clustering of Distributed Databases Considering Privacy Preservation

    Katsuhiro HONDA, Kohei KUNISAWA, Seiki UBUKATA, Akira NOTSU

    Journal of Japan Society for Fuzzy Theory and Intelligent Informatics   33 ( 2 )   600 - 607   2021.05( ISSN:1347-7986 ( eISSN:1881-7203

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    Publishing type:Research paper (scientific journal)  

    DOI: 10.3156/jsoft.33.2_600

  • ノイズファジィクラスタリング機構に基づくロバスト非負値行列分解と環境観測値分析への応用 Reviewed

    本多 克宏,上野 雅哲,生方 誠希,野津 亮

    日本知能情報ファジィ学会誌 雑誌   33 ( 2 )   593 - 599   2021.05

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    Kind of work:Joint Work  

  • プライバシー保護を考慮した分散データベースの線形ファジィクラスタリング Reviewed

    本多 克宏,國澤 昂平,生方 誠希,野津 亮

    日本知能情報ファジィ学会誌 雑誌   33 ( 2 )   600 - 607   2021.05

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    Kind of work:Joint Work  

  • Objective function-based rough membership C-means clustering Reviewed

    S. Ubukata, A. Notsu, K. Honda

    Information Sciences 雑誌   548   479 - 496   2021.02

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    Kind of work:Joint Work  

  • Online state space generation by a growing self-organizing map and differential learning for reinforcement learning Reviewed

    A. Notsu, K. Yasuda, S. Ubukata, K. Honda

    Applied Soft Computing Journal 雑誌   97 ( 2 )   2020.12

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    Kind of work:Joint Work  

  • Noise Rejection Approaches for Various Rough Set-Based C-Means Clustering

    Seiki Ubukata, Sho Sekiya, Akira Notsu, Katsuhiro Honda

    Journal of Advanced Computational Intelligence and Intelligent Informatics   24 ( 6 )   738 - 749   2020.11( ISSN:1343-0130 ( eISSN:1883-8014

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    Publishing type:Research paper (scientific journal)  

    In the field of cluster analysis, rough set-based extensions of hard <italic>C</italic>-means (HCM; <italic>k</italic>-means) including rough <italic>C</italic>-means (RCM), rough set <italic>C</italic>-means (RSCM), and rough membership <italic>C</italic>-means (RMCM) are promising approaches for dealing with the certainty, possibility, uncertainty of belonging of object to clusters. Since <italic>C</italic>-means-type methods are strongly affected by noise, noise clustering approaches have been proposed. In noise clustering approaches, noise objects, which are far from any cluster center, are rejected for robust estimation. In this paper, we introduce noise rejection approaches for rough set-based <italic>C</italic>-means based on probabilistic memberships and propose noise RCM with membership normalization (NRCM-MN), noise RSCM with membership normalization (NRSCM-MN), and noise RMCM (NRMCM). In addition, visualization demonstration of the cluster boundaries on the two-dimensional plane of the proposed methods is carried out to confirm the characteristics of each method. Furthermore, the clustering performance is verified by numerical experiments using real-world datasets.

    DOI: 10.20965/jaciii.2020.p0738

  • 混合多項分布型ファジィ共クラスタリングにおけるクラスター数の自動設定法 Reviewed

    生方誠希,柳澤和輝,野津亮,本多克宏

    日本知能情報ファジィ学会誌 雑誌   32 ( 2 )   678 - 685   2020.02

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    Kind of work:Joint Work  

  • Visualization of Potential Technical Solutions by SOM and Co-clustering and Its Extension to Multi-view Situation Reviewed

    Y. Nishida, K. Honda

    Journal of Advanced Computational Intelligence and Intelligent Informatics 雑誌   24 ( 1 )   65 - 72   2020.01

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    Kind of work:Joint Work  

  • A Heuristic-based Model for MMMs-induced Fuzzy Co-clustering with Dual Exclusive Partition Reviewed

    K. Honda, Y. Hakui, S. Ubukata, A. Notsu

    Journal of Advanced Computational Intelligence and Intelligent Informatics 雑誌   24 ( 1 )   40 - 47   2020.01

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    Kind of work:Joint Work  

  • Visual Co-cluster Assessment with Intuitive Cluster Validation through Cooccurrence-Sensitive Ordering Reviewed

    K. Honda, T. Sako, S. Ubukata, A. Notsu

    Journal of Advanced Computational Intelligence and Intelligent Informatics 雑誌   22 ( 5 )   585 - 592   2018.09

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    Kind of work:Joint Work  

  • Spectral Ordering に基づく共クラスタ構造の視覚化とその特徴 Reviewed

    佐古拓也, 本多克宏, 生方誠希, 野津 亮

    システム制御情報学会論文誌 雑誌   31 ( 5 )   177 - 183   2018.05

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    Kind of work:Joint Work  

  • Deterministic Annealing Process for pLSA-induced Fuzzy Co-clustering and Cluster Splitting Characteristics Reviewed

    T. Goshima, K. Honda, S. Ubukata, A. Notsu

    International Journal of Approximate Reasoning 雑誌   95   185 - 193   2018.04

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    Kind of work:Joint Work  

  • FCM-type Fuzzy Coclustering for Three-mode Cooccurrence Data: 3FCCM and 3Fuzzy CoDoK Reviewed

    K. Honda, Y. Suzuki, S. Ubukata, A. Notsu

    Advances in Fuzzy Systems 雑誌   9842127   1 - 8   2017.12

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    Kind of work:Joint Work  

  • Noise Rejection in MMMs-induced Fuzzy Co-clustering Reviewed

    K. Honda, N. Yamamoto, S. Ubukata, A. Notsu

    Journal of Advanced Computational Intelligence and Intelligent Informatics 雑誌   21 ( 7 )   1144 - 1151   2017.11

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    Kind of work:Joint Work  

  • Fuzzy Clustering-based k-anonymization of Eigen-face Features for Crowd Movement Analysis with Privacy Consideration Reviewed

    K. Honda, M. Omori, S. Ubukata, A. Notsu

    International Journal of Innovative Computing, Information and Control 雑誌   12 ( 4 )   1375 - 1384   2016.08

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    Kind of work:Joint Work  

  • A Semi-supervised Framework for MMMs-induced Fuzzy Co-clustering with Virtual Samples Reviewed

    D. Tanaka, K. Honda, S. Ubukata, A. Notsu

    Advances in Fuzzy Systems 雑誌   2016 ( 5206048 )   1 - 8   2016.06

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    Kind of work:Joint Work  

  • ファジィk-memberクラスタリングによる顔画像匿名化を伴うプライバシー保護群集行動分析 Reviewed

    本多克宏, 大森正博, 生方誠希, 野津亮

    システム制御情報学会論文誌 雑誌   29 ( 3 )   130 - 135   2016.03

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    Kind of work:Joint Work  

  • Fuzzy Co-clustering Induced by Multinomial Mixture Models Reviewed

    K. Honda, S. Oshio, A. Notsu

    Journal of Advanced Computational Intelligence and Intelligent Informatics 雑誌   19 ( 6 )   717 - 726   2015.11

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    Kind of work:Joint Work  

  • Partially Exclusive Item Partition in MMMs-induced Fuzzy Co-clustering and Its Effects in Collaborative Filtering Reviewed

    K. Honda, T. Nakano, C.-H. Oh, S. Ubukata, A. Notsu

    Journal of Advanced Computational Intelligence and Intelligent Informatics 雑誌   19 ( 6 )   810 - 817   2015.11

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    Kind of work:Joint Work  

  • A Collaborative Framework for Privacy Preserving Fuzzy Co-clustering of Vertically Distributed Cooccurrence Matrices Reviewed

    K. Honda, T. Oda, D. Tanaka, A. Notsu

    Advances in Fuzzy Systems 雑誌   2015 ( 729072 )   1 - 8   2015.03

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    Kind of work:Joint Work  

  • Alternative c-Means基準を用いたロバストな局所的主成分分析による多次元データの2次元視覚化 Reviewed

    中尾索也, 本多克宏, 野津 亮

    日本知能情報ファジィ学会誌 雑誌   26 ( 3 )   718 - 727   2014.06

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    Kind of work:Joint Work  

  • Performance Comparison of Collaborative Filtering with k-Anonymized Data by Fuzzy k-Member Clustering Reviewed

    A. Kawano, K. Honda, A. Notsu, H. Ichihashi

    Journal of Advanced Computational Intelligence and Intelligent Informatics 雑誌   18 ( 2 )   239 - 245   2014.03

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    Kind of work:Joint Work  

  • 向きに依存した不確実性を考慮したスイッチング回帰モデルと太陽光発電データの分析への応用 Reviewed

    岩田俊介, 本多克宏, 野津 亮

    システム制御情報学会論文誌 雑誌   27 ( 2 )   29 - 35   2014.01

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    Kind of work:Joint Work  

  • A Greedy Algorithm for k-Member Co-clustering and Its Applicability to Collaborative Filtering Reviewed

    K. Honda, A. Kawano, H. Kasugai, A. Notsu

    Procedia Computer Science 雑誌   22   477 - 484   2013.09

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    Kind of work:Joint Work  

  • Visualization of Non-Euclidean Relational Data by Robust Linear Fuzzy Clustering Based on FCMdd Framework Reviewed

    K. Honda, T. Yamamoto, A. Notsu, H. Ichihashi

    Journal of Advanced Computational Intelligence and Intelligent Informatics 雑誌   17 ( 2 )   312 - 317   2013.03

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    Kind of work:Joint Work  

  • FCMdd型線形ファジィクラスタリングによる非ユークリッド関係性データからの局所的マップ構築 Reviewed

    山本剛史, 本多克宏, 野津 亮, 市橋秀友

    日本知能情報ファジィ学会誌 雑誌   24 ( 3 )   821 - 825   2012.06

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    Kind of work:Joint Work  

  • A Comparative Study on TIBA Imputation Methods in FCMdd-Based Linear Clustering with Relational Data Reviewed

    T. Yamamoto, K. Honda, A. Notsu, H. Ichihashi

    Advances in Fuzzy Systems 雑誌   2011 ( 265170 )   1 - 10   2011.10

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    Kind of work:Joint Work  

  • Non-Euclidean Extension of FCMdd-based Linear Clustering for Relational Data Reviewed

    T. Yamamoto, K. Honda, A. Notsu, H. Ichihashi

    Journal of Advanced Computational Intelligence and Intelligent Informatics 雑誌   15 ( 8 )   1050 - 1056   2011.10

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    Kind of work:Joint Work  

  • VariableWeighting in PCA-Guided k-Means and Its Connection with Information Summarization Reviewed

    K. Honda, A. Notsu, H. Ichihashi

    Journal of Advanced Computational Intelligence and Intelligent Informatics 雑誌   15 ( 1 )   83 - 89   2011.01

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    Kind of work:Joint Work  

  • 逐次的クラスタ抽出に基づく協調フィルタリングの改良型アルゴリズム Reviewed

    本多克宏, 野津 亮, 市橋秀友

    システム制御情報学会論文誌 雑誌   23 ( 12 )   288 - 290   2010.12

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    Kind of work:Joint Work  

  • Fuzzy PCA-guided Robust k-Means Clustering Reviewed

    K. Honda, A. Notsu, H. Ichihashi

    IEEE Transactions on Fuzzy Systems   18 ( 1 )   67 - 79   2010.02

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    Kind of work:Joint Work  

  • 逐次的なユーザ・アイテムクラスタ抽出に基づく協調フィルタリング Reviewed

    本多克宏, 野津 亮, 市橋秀友

    システム制御情報学会論文誌   22 ( 10 )   364 - 370   2009.10

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    Kind of work:Joint Work  

  • Fuzzy c-Medoids法の応用による線形クラスタリングと関係データからの部分空間学習 Reviewed

    垪和直樹, 本多克宏, 市橋秀友, 野津 亮

    日本知能情報ファジィ学会誌 雑誌   21 ( 1 )   151 - 159   2009.02

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    Kind of work:Joint Work  

  • 最適尺度法に基づく尺度混在データのためのFCM型スイッチング回帰モデル Reviewed

    本多克宏, 市橋秀友, 野津 亮

    システム制御情報学会論文誌 雑誌   21 ( 8 )   269 - 275   2008.08

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    Kind of work:Joint Work  

  • 段階的可能性アプローチを用いた局所的な数量化分析法によるアンケートデータの分析 Reviewed

    呉 志賢, 本多克宏, 市橋秀友, 牧瀬太一

    日本知能情報ファジィ学会誌 雑誌   20 ( 2 )   255 - 264   2008.04

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    Kind of work:Joint Work  

  • Linear Fuzzy Clustering With Selection of Variables Using Graded Possibilistic Approach Reviewed

    K. Honda, H. Ichihashi, F. Masulli, S. Rovetta

    IEEE Transactions on Fuzzy Systems 雑誌   15 ( 5 )   878 - 889   2007.10

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    Kind of work:Joint Work  

  • 逐次学習を伴う線形ファジィクラスタリングによる適応的な協調フィルタリング Reviewed

    本多克宏, 市橋秀友, 野津 亮

    システム制御情報学会論文誌 雑誌   20 ( 7 )   283 - 291   2007.07

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    Kind of work:Joint Work  

  • 線形ファジィクラスタリングに基づく混合データベースの局所的な主成分分析 Reviewed

    上杉 亮, 本多克宏, 市橋秀友, 野津 亮

    日本知能情報ファジィ学会誌 雑誌   19 ( 3 )   287 - 298   2007.06

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    Kind of work:Joint Work  

  • FCM-type Fuzzy Clustering of Mixed Databases Considering Nominal Variable Quantification Reviewed

    K. Honda, R. Uesugi, H. Ichihashi

    Journal of Advanced Computational Intelligence and Intelligent Informatics 雑誌   11 ( 2 )   162 - 167   2007.02

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    Kind of work:Joint Work  

  • A Regularization Approach to Fuzzy Clustering with Nonlinear Membership Weights Reviewed

    K. Honda, H. Ichihashi

    Journal of Advanced Computational Intelligence and Intelligent Informatics 雑誌   11 ( 1 )   28 - 34   2007.01

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    Kind of work:Joint Work  

  • Quantification of Multivariate Categorical Data Considering Typicality of Item Reviewed

    C.-H. Oh, K. Honda and H. Ichihashi

    Journal of Advanced Computational Intelligence and Intelligent Informatics 雑誌   11 ( 1 )   35 - 39   2007.01

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    Kind of work:Joint Work  

  • 外的基準の説明を目的とした独立成分分析 Reviewed

    本多克宏, 前中達矢, 市橋秀友

    システム制御情報学会論文誌 雑誌   19 ( 9 )   358 - 364   2006.09

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    Kind of work:Joint Work  

  • Fuzzy Local Independent Component Analysis with External Criteria and Its Application to Knowledge Discovery in Databases Reviewed

    K. Honda, H. Ichihashi

    International Journal of Approximate Reasoning 雑誌   42 ( 3 )   159 - 173   2006.08

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    Kind of work:Joint Work  

  • 混合データベースのFCMクラスタリング Reviewed

    本多克宏, 上杉 亮, 市橋秀友

    日本知能情報ファジィ学会誌 雑誌   18 ( 4 )   598 - 608   2006.08

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    Kind of work:Joint Work  

  • ファジィクラスタリングを用いた主成分分析における変量選択とデータマイニングへの応用 Reviewed

    本多克宏, 市橋秀友

    システム制御情報学会論文誌 雑誌   18 ( 9 )   322 - 330   2005.09

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    Kind of work:Joint Work  

  • Regularized Linear Fuzzy Clustering and Probabilistic PCA Mixture Models Reviewed

    K. Honda, H. Ichihashi

    IEEE Transactions on Fuzzy Systems 雑誌   13 ( 4 )   508 - 516   2005.08

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    Kind of work:Joint Work  

  • 外的基準がある場合の独立成分分析と局所的モデリングへの拡張 Reviewed

    本多克宏, 下村直也, 市橋秀友

    システム制御情報学会論文誌 雑誌   17 ( 10 )   459 - 467   2004.10

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    Kind of work:Joint Work  

  • Component-wise Robust Linear Fuzzy Clustering for Collaborative Filtering Reviewed

    K. Honda, H. Ichihashi

    International Journal of Approximate Reasoning 雑誌   37 ( 2 )   127 - 144   2004.09

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    Kind of work:Joint Work  

  • Simultaneous Application of Fuzzy Clustering and Quantification with Incomplete Categorical Data Reviewed

    K. Honda, Y. Nakamura, H. Ichihashi

    Journal of Advanced Computational Intelligence and Intelligent Informatics 雑誌   8 ( 4 )   397 - 402   2004.07

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    Kind of work:Joint Work  

  • K-L情報量正則化を用いた線形ファジィクラスタリング法 Reviewed

    本多克宏, 神田章裕, 市橋秀友

    日本知能情報ファジィ学会誌 雑誌   15 ( 6 )   682 - 692   2003.12

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    Kind of work:Joint Work  

  • FCV法の一般化と最小絶対誤差に基づくロバストなシェルクラスタリング Reviewed

    本多克宏, 東江伸浩, 市橋秀友

    日本知能情報ファジィ学会誌 雑誌   15 ( 6 )   693 - 701   2003.12

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    Kind of work:Joint Work  

  • ロバストな線形ファジィクラスタリング法の提案と協調フィルタリングシステムへの応用 Reviewed

    本多克宏, 杉浦伸和, 市橋秀友

    システム制御情報学会論文誌 雑誌   16 ( 11 )   597 - 605   2003.11

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    Kind of work:Joint Work  

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Books and Other Publications

MISC

  • Preface

    Honda K.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   14376 LNAI   v - vi   2023( ISSN:03029743 ( ISBN:9783031467806

Presentations

  • A Local PCA Model Induced from Linear Fuzzy Clustering With Cluster Separation International conference

    Katsuhiro Honda, Daichi Machida, Seiki Ubukata, Akira Notsu

    International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making  2025.03 

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    Presentation type:Oral presentation (general)  

  • Utilization of Genre Information in Collaborative Filtering by Three-mode Fuzzy Co-Clustering International conference

    Katsuhiro Honda, Haruto Miwa, Seiki Ubukata, Akira Notsu

    2024 Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on Advanced Intelligent Systems (SCIS&amp;amp;ISIS)  2024.11  IEEE

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    Presentation type:Oral presentation (general)  

    DOI: 10.1109/scisisis61014.2024.10760181

  • Extension of Fuzzy c-Lines Considering Compactness and Separation of Clusters International conference

    Katsuhiro Honda, Daichi Machida, Seiki Ubukata, Akira Notsu

    2024 Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on Advanced Intelligent Systems (SCIS&amp;amp;ISIS)  2024.11  IEEE

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    Presentation type:Oral presentation (general)  

    DOI: 10.1109/scisisis61014.2024.10759916

  • Horizontally Distributed Sensor Data Analysis by Linear Fuzzy Clustering Based on Federated Learning Domestic conference

    Amejima Ryosuke, Honda Katsuhiro, Ubukata Seiki, Notsu Akira

    Proceedings of the Fuzzy System Symposium  2024.09  Japan Society for Fuzzy Theory and Intelligent Informatics

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    Presentation type:Oral presentation (general)  

    <p>Federated learning is a scheme of analyzing distributed data by preserving personal privacy and has been applied to fuzzy clustering. In this paper, federated learning-based linear fuzzy clustering is applied to a horizontally distributed sensor data, where characteristics of the federated learning model is discussed through comparison with the batch learning result.</p>

    DOI: 10.14864/fss.40.0_143

  • A Study on Additional Information Utilization in Collaborative Filtering by Three-mode Co-clustering Domestic conference

    Miwa Haruto, Honda Katsuhiro, Ubukata Seiki, Notsu Akira

    Proceedings of the Fuzzy System Symposium  2024.09  Japan Society for Fuzzy Theory and Intelligent Informatics

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    <p>The performance of collaborative filtering (CF) can be improved by utilizing not only user-item cooccurrence information but also additional information. This paper improves co-clustering-based CF by introducing three-mode fuzzy co-clustering, which utilizes the conventional user-item cooccurrence information in conjunction with additional genre information on each item. User-item co-clusters are extracted so that preference tendencies of users on items are considered with their intrinsic preferences on genre categories. Then, the recommendation capability of co-clustering-based CF is expected to be improved even when cooccurrence information is quite sparse. In numerical experiments with MovieLens benchmark data, recommendation performance is demonstrated to be improved by properly increasing the responsibility degree of genre information.</p>

    DOI: 10.14864/fss.40.0_146

  • Basic Consideration of Collaborative Filtering Based on Rough Membership C-Means Clustering with Noise Rejection Mechanism Domestic conference

    Hayashi Ryoya, Ubukata Seiki, Honda Katsuhiro

    Proceedings of the Fuzzy System Symposium  2024.09  Japan Society for Fuzzy Theory and Intelligent Informatics

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    <p>In clustering-based collaborative filtering (CF), clusters of users with similar preference patterns are extracted, and highly preferred items within these clusters are recommended. Since the data used in CF tasks contain uncertainties due to human sensitivities, rough clustering based on rough set theory, which handles these uncertainties, is considered effective. Thus, RMCM-CF, a CF method based on rough membership C-means (RMCM) clustering, a type of rough clustering, has been proposed. In this study, we examine NRMCM-CF, a CF method based on noise RMCM, which incorporates a noise rejection mechanism into RMCM. In NRMCM-CF, uncertainty is considered using rough membership values, which are the proportions of clusters in the neighborhoods of objects, and objects far from any cluster center are removed as noise to achieve robust recommendations. Additionally, we verify the recommendation performance of the proposed method through numerical experiments using real-world datasets.</p>

    DOI: 10.14864/fss.40.0_472

  • Basic Consideration of Rough Set C-Means Clustering with Missing Value Processing and Its Application to Collaborative Filtering Domestic conference

    Futakuchi Kazushi, Ubukata Seiki, Honda Katsuhiro

    Proceedings of the Fuzzy System Symposium  2024.09  Japan Society for Fuzzy Theory and Intelligent Informatics

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    Presentation type:Oral presentation (general)  

    <p>In clustering-based collaborative filtering (CF), clusters of users with similar preference patterns are extracted, and highly preferred items withinthese clusters are recommended. Since the data used in CF tasks contain uncertainties due to human sensitivities, rough clustering based onrough set theory, which handles these uncertainties, is considered effective. Thus, RSCM-CF, a CF method based on rough set C-means (RSCM)clustering, a type of rough clustering, has been proposed. In this study, we propose RSCM-PDS, an RSCM method incorporating missing valueprocessing using the partial distance strategy (PDS) and examine its application to collaborative filtering as RSCM-PDS-CF. In RSCM-PDS,effective cluster analysis is expected by calculating distances based on dimensions with common values between vectors containing missingvalues. Additionally, we verify the recommendation performance of the proposed method through numerical experiments using real-worlddatasets.</p>

    DOI: 10.14864/fss.40.0_328

  • Improved Linear Fuzzy Clustering Considering Compactness and Separation Domestic conference

    Machida Daichi, Honda Katsuhiro, Ubukata Seiki, Notsu Akira

    Proceedings of the Fuzzy System Symposium  2024.09  Japan Society for Fuzzy Theory and Intelligent Informatics

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    <p>Fuzzy Compactness and Separation (FCS) is an extension of Fuzzy c-Means (FCM) for finding compact but separate clusters with the combined objective function of the FCM aggregation criterion and the cluster separation measure. This paper further extends FCS to linear fuzzy clustering by replaceing FCM prototypes with lines such that the clustering criterion of Fuzzy c-Lines (FCL) is combined with the degree of cluster distortion measuring the distances among each data object and the global centroid. Experimental results demonstrate that the initialization sensitivity can be improved by introducing the separation criterion in linear fuzzy clustering.</p>

    DOI: 10.14864/fss.40.0_468

  • ファジィ度調節機構を導入したRough Membership C-Meansクラスタリングとその協調フィルタリングへの応用 Domestic conference

    得原 一馬, 生方 誠希, 本多 克宏

    2024インテリジェントシステムシンポジウム  2024.09 

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  • ノイズファジィクラスタリングに基づくロバストなスイッチングFactorization Machine Domestic conference

    大同 陸渡,本多 克宏,生方 誠希,野津 亮

    2024インテリジェントシステムシンポジウム  2024.09 

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    Presentation type:Oral presentation (general)  

  • 楕円体状クラスタリングを用いたANFISにおける入出力ノイズ観測値の処理 Domestic conference

    倉橋 隆太, 本多 克宏, 生方 誠希, 野津 亮

    2024インテリジェントシステムシンポジウム  2024.09 

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    Presentation type:Oral presentation (general)  

  • 限定された探索回数条件下でのJADEの個体数制御 Domestic conference

    松木 智哉, 野津 亮, 本多 克宏

    2024インテリジェントシステムシンポジウム  2024.09 

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    Presentation type:Oral presentation (general)  

  • Control of JADE Population in Limited Number of Searches for Realistic Situations International conference

    Tomoya Matsuki, Akira Notsu, Katsuhiro Honda, Takuya Kato, Masakazu Shibahara

    2024 IEEE Congress on Evolutionary Computation  2024.07 

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  • FCM-Induced Switching Reinforcement Learning for Collaborative Learning International conference

    Katsuhiro Honda, Taimu Yaotome, Seiki Ubukata, Akira Notsu

    International Joint Conference on Neural Networks  2024.07 

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  • FCM法に基づくスイッチング強化学習 Domestic conference

    八乙女 大夢, 本多 克宏, 生方 誠希, 野津 亮

    システム制御情報学会 研究発表講演会  2024.05 

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  • FCM法に基づくANFISにおける連合学習 Domestic conference

    湊 大輝, 本多 克宏, 生方 誠希, 野津 亮

    システム制御情報学会 研究発表講演会  2024.05 

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  • ファジィクラスタリングとの融合によるマルチエージェント強化学習 Domestic conference

    八乙女 大夢,本多 克宏,生方 誠希,野津 亮

    2023年度計測自動制御学会関西支部・システム制御情報学会シンポジウム  2024.01 

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  • ファジィクラスタリングによるANFISの連合学習に関する一考察 Domestic conference

    湊 大輝,本多 克宏,生方 誠希,野津 亮

    2023年度計測自動制御学会関西支部・システム制御情報学会シンポジウム  2024.01 

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    Presentation type:Oral presentation (general)  

  • Genre-weighted Fuzzy Co-clustering and Its Application to Personalized Recommendation Domestic conference

    Q. Cochet, K. Honda, S. Ubukata, A. Notsu

    2023年度計測自動制御学会関西支部・システム制御情報学会シンポジウム  2024.01 

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    Presentation type:Oral presentation (general)  

  • Robust ANFIS Classifier Based on Noise Fuzzy Clustering with Softmax Normalization International conference

    K. Kitamori, K. Honda, S. Ubukata, A. Notsu

    24th International Symposium on Advanced Intelligent Systems  2023.12 

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  • Collaborative Filtering Based on Rough Set C-Means Clustering with Noise Rejection Mechanism International conference

    S. Ubukata, R. Hayashi, K. Honda

    24th International Symposium on Advanced Intelligent Systems  2023.12 

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  • A Federated Learning Model for Linear Fuzzy Clustering with Least Square Criterion International conference

    K. Honda, R. Amejima

    International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making  2023.11 

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  • Basic Consideration of Adaptive Mini-Batch Rough C-Means Clustering and Its Application to Collaborative Filtering Domestic conference

    Kawakami Tomohiro, Ubukata Seiki, Honda Katsuhiro

    2023.11 

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  • A Study on Robust ANFIS Classifier Based on Noise Fuzzy Clustering Domestic conference

    Kitamori Koki, Honda Katsuhiro, Ubukata Seiki, Notsu Akira

    2023.11 

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  • Fuzzy c-Lines法のための水平分散型の連合学習モデル Domestic conference

    本多 克宏, 雨嶋 亮介, 生方 誠希, 野津 亮

    第39回ファジィシステムシンポジウム  2023.09 

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  • 部分的距離戦略を用いた不完全データのためのスイッチング非負値行列分解 Domestic conference

    岡部 旭良, 本多 克宏, 生方 誠希, 野津 亮

    第39回ファジィシステムシンポジウム  2023.09 

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    Presentation type:Oral presentation (general)  

  • FCM-Induced Switching Fuzzy Factorization Machine for Collaborative Filtering International conference

    R. Daido, K. Honda, S. Ubukata, A. Notsu

    IEEE International Conference on Fuzzy Systems  2023.08 

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  • Handling of Component-Wise Noise in ANFIS Induced by Ellipsoidal Fuzzy Clustering International conference

    K. Honda, R. Kurahashi, S. Ubukata, A. Notsu

    IEEE International Conference on Fuzzy Systems  2023.08 

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  • 楕円体状クラスタリングを用いたANFISネットワークの前件部構築の改良 Domestic conference

    倉橋 隆太,本多 克宏,生方 誠希,野津 亮

    第67回システム制御情報学会研究発表講演会  2023.05 

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  • k-Means 型スイッチングFactorization Machine による協調フィルタリング Domestic conference

    大同 陸渡,本多 克宏,生方 誠希,野津 亮

    第67回システム制御情報学会研究発表講演会  2023.05 

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  • Basic Consideration of Collaborative Filtering Based on Rough Co-clustering Induced by Multinomial Mixture Models International conference

    S. Ubukata, K. Mouri, K. Honda

    2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems  2022.11 

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  • Adaptive Online Rough C-Means Clustering and Its Application to Collaborative Filtering International conference

    S. Ubukata, T. Kawakami, K. Honda

    2022 IEEE Symposium Series on Computational Intelligence  2022.11 

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  • Handling of Missing Values in FCM Clustering-based ANFIS with Partial Distance Strategy International conference

    K. Honda, S. Hyakutake, S. Ubukata, A. Notsu

    2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems  2022.11 

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  • Fuzzy c-Lines for Vertically Distributed Database with Missing Values International conference

    K. Kunisawa, K. Honda, S. Ubukata, A. Notsu

    2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems  2022.11 

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  • Algorithm of Fuzzy Clustering and Application to Local Data Analysis Invited International conference

    K. Honda

    The 10th International Symposium on Computational Intelligence and Industrial Applications  2022.09 

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    Presentation type:Oral presentation (invited, special)  

  • A Noise Clustering-induced Robust Adaptive Network-based Fuzzy Inference System for Classification International conference

    K. Honda, K. Kitamori, S. Ubukata, A. Notsu

    2022 International Joint Conference on Neural Networks  2022.07 

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  • A Comparative Study on Utilization of Semantic Information in Fuzzy Co-clustering International conference

    Yusuke Takahata, Katsuhiro Honda, Seiki Ubukata

    International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making  2022.03 

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  • Noise Fuzzy Clustering-Based Robust Non-negative Matrix Factorization with I-divergence Criterion International conference

    Akira Okabe, Katsuhiro Honda, Seiki Ubukata

    International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making  2022.03 

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Outline of collaborative research (seeds)

  • k匿名化によるプライバシー保護データ解析

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    クラスタリングによるk匿名化による安心安全なデータ解析に関する研究

  • クラスタリングに基づく協調フィルタリング

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    個人履歴情報の要約手法と協調フィルタリングへの応用に関する研究

  • ヒューマンインターフェースの改善法の研究

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    多次元データの低次元化によるヒューマンインターフェースの改善法の研究

  • クラスタリングに基づく知識発見手法

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    クラスタリングに基づく知識発見手法と天候データを用いた販売予測の研究

Grant-in-Aid for Scientific Research

  • Advanced Study on Flexible Recommendation Systems Based on Clustering Considering Uncertainty

    Grant-in-Aid for Scientific Research(C)  2026

  • 強化学習における政策・時空間・ハイパーパラメータの分節化と最適化,その統合

    Grant-in-Aid for Scientific Research(C)  2025

  • Advanced Study on Flexible Recommendation Systems Based on Clustering Considering Uncertainty

    Grant-in-Aid for Scientific Research(C)  2025

  • 強化学習における政策・時空間・ハイパーパラメータの分節化と最適化,その統合

    Grant-in-Aid for Scientific Research(C)  2024

  • Advanced Study on Flexible Recommendation Systems Based on Clustering Considering Uncertainty

    Grant-in-Aid for Scientific Research(C)  2024

  • 協調的なファジィクラスタリングと説明可能AIに関する研究

    Grant-in-Aid for Scientific Research(C)  2024

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Charge of on-campus class subject

  • エンジニアのためのキャリアデザイン/経営論

    2024   Weekly class   Undergraduate

  • データ解析

    2024   Weekly class   Undergraduate

  • システム工学

    2024   Weekly class   Undergraduate

  • 情報工学実験1

    2024   Weekly class   Undergraduate

  • 情報工学基礎演習1

    2024   Weekly class   Undergraduate

  • データマイニング

    2024   Weekly class   Graduate school

  • 基幹情報学特別研究2

    2024   Intensive lecture   Graduate school

  • 基幹情報学特別研究1

    2024   Intensive lecture   Graduate school

  • 基幹情報学特別演習I-1

    2024   Intensive lecture   Graduate school

  • 基幹情報学特別研究8

    2024   Intensive lecture   Graduate school

  • 基幹情報学特別研究7

    2024   Intensive lecture   Graduate school

  • 基幹情報学特別研究5

    2024   Intensive lecture   Graduate school

  • 基幹情報学特別研究3

    2024   Intensive lecture   Graduate school

  • 人間情報システム特別講義

    2024   Weekly class   Graduate school

  • 情報セキュリティ

    2024   Weekly class   Undergraduate

  • 情報工学実験2

    2024   Weekly class   Undergraduate

  • 情報工学基礎演習2

    2024   Weekly class   Undergraduate

  • 基幹情報学特別演習2

    2024   Weekly class   Graduate school

  • 基幹情報学セミナー

    2024   Weekly class   Graduate school

  • 基幹情報学特別研究2

    2024   Intensive lecture   Graduate school

  • 基幹情報学特別研究1

    2024   Intensive lecture   Graduate school

  • 基幹情報学特別演習I-2

    2024   Intensive lecture   Graduate school

  • 基幹情報学特別研究8

    2024   Intensive lecture   Graduate school

  • 基幹情報学特別研究6

    2024   Intensive lecture   Graduate school

  • 基幹情報学特別研究4

    2024   Intensive lecture   Graduate school

  • Recent Advances in Engineering

    2021    

  • Engineering Ethics for Engineers

    2021    

  • Engineering Ethics for Engineers

    2021    

  • Systems Engineering

    2021    

  • Fundamentals in Electrical and Electronic Engineering I

    2021    

  • Fundamentals in Electrical and Electronic Engineering I

    2021    

  • Advanced Human Information Systems

    2021    

  • Advanced Intelligent Information Systems I

    2021    

  • Selected Topics in Human Information Systems

    2021    

  • Laboratory in Computer Science I

    2021   Practical Training  

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Visiting Lectures ⇒ Link to the list of Visiting Lectures

  • データマイニングのためのクラスター分析

    Category:Engineering (machinery, electronics / physics, electrical / electronics, electrical information, chemical biotechnology, architecture, cities (civil engineering / environment), material chemistry, aerospace, marine systems, applied chemistry, chemistry, materials)

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    Audience:High school students, College students, General

    Keyword:データマイニング, 知識発見, クラスター分析 

    店舗での販売時点情報(POSデータ)やネットコミュニティでの履歴情報などのデータベースからヒトにとって有益な知識を得るためのデータマイニングを目的に、クラスター分析の概念と活用方法について解説します。

Job title

  • Job title within the department

    School of Engineering Department of Information Science 

    学科長  2022.04 - 2024.03