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Comparison of Fuzzy Co-clustering Methods in Collaborative Filtering-Based Recommender System

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Modeling Decisions for Artificial Intelligence (MDAI 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10571))

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Abstract

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.

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Acknowledgment

This work was supported by JSPS KAKENHI Grant Number 15K00348.

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Authors and Affiliations

  1. Shibaura Institute of Technology, Koto, Tokyo, 135-8548, Japan

    Tadafumi Kondo & Yuchi Kanzawa

Authors
  1. Tadafumi Kondo
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  2. Yuchi Kanzawa
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Corresponding author

Correspondence to Tadafumi Kondo .

Editor information

Editors and Affiliations

  1. University of Skövde, Skövde, Sweden

    Vicenç Torra

  2. Toho Gakuen, Kunitachi, Tokyo, Japan

    Yasuo Narukawa

  3. Kyushu Institute of Technology, Iizuka, Fukuoka, Japan

    Aoi Honda

  4. Kyushu Institute of Technology, Kitakyushu-shi, Fukuoka, Japan

    Sozo Inoue

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Kondo, T., Kanzawa, Y. (2017). Comparison of Fuzzy Co-clustering Methods in Collaborative Filtering-Based Recommender System. In: Torra, V., Narukawa, Y., Honda, A., Inoue, S. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2017. Lecture Notes in Computer Science(), vol 10571. Springer, Cham. https://doi.org/10.1007/978-3-319-67422-3_10

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  • DOI: https://doi.org/10.1007/978-3-319-67422-3_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67421-6

  • Online ISBN: 978-3-319-67422-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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