Collaborative filtering analysis of consumption behavior based on the latent class model

Manabu Kobayashi, Kenta Mikawa, Masayuki Goto, Shigeichi Hirasawa

    研究成果: Conference contribution

    抄録

    In this manuscript, we investigate a collaborative filtering method to characterize consumption behavior (or evaluation) of customers (or users) and services (or items) for marketing. Assuming that each customer and service have the invisible attribute, which is called latent class, we propose a new Bayesian statistical model that consumption behavior is probabilistically arise based on a latent class combination of a customer and service. Then, we show the method to estimate parameters of a statistical model based on the variational Bayes method and the mean field approximation. Consequently, we show the effectiveness of the proposed model and the estimation method by simulation and analyzing actual data.

    本文言語English
    ホスト出版物のタイトル2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
    出版社Institute of Electrical and Electronics Engineers Inc.
    ページ1926-1931
    ページ数6
    2017-January
    ISBN(電子版)9781538616451
    DOI
    出版ステータスPublished - 2017 11 27
    イベント2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017 - Banff, Canada
    継続期間: 2017 10 52017 10 8

    Other

    Other2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
    国/地域Canada
    CityBanff
    Period17/10/517/10/8

    ASJC Scopus subject areas

    • 人工知能
    • コンピュータ サイエンスの応用
    • 人間とコンピュータの相互作用
    • 制御と最適化

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