Comparison of fuzzy co-clustering methods in collaborative filtering-based recommender system

Tadafumi Kondo, Yuchi Kanzawa

研究成果: Conference contribution

抄録

Various fuzzy co-clustering methods have been proposed for collaborative filtering; however, it is not clear which method is best in terms of accuracy. This paper proposes a recommender system that utilizes fuzzy co-clustering-based collaborative filtering and also evaluates four fuzzy co-clustering methods. The proposed system recommends optimal items to users using large-scale rating datasets. The results of numerical experiments conducted using one artificial dataset and two real datasets indicate that, the proposed method combined with a particular fuzzy co-clustering method is more accurate than conventional methods.

本文言語English
ホスト出版物のタイトルModeling Decisions for Artificial Intelligence - 14th International Conference, MDAI 2017, Proceedings
編集者Aoi Honda, Yasuo Narukawa, Vicenc Torra, Sozo Inoue
出版社Springer Verlag
ページ103-116
ページ数14
ISBN(印刷版)9783319674216
DOI
出版ステータスPublished - 2017
イベント14th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2017 - Kitakyushu, Japan
継続期間: 2017 10 182017 10 20

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
10571 LNAI
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Other

Other14th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2017
国/地域Japan
CityKitakyushu
Period17/10/1817/10/20

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

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