Construction of recommender system based on cognitive model for "self-reflection"

    研究成果: Conference contribution

    抜粋

    Every human processes a set of mental schemas for problem solving. We develop and improve these schemas by reflecting on our experiences with errors, which is a type of metacognition (Kayashima, 2008). In this study, we proposed a cognitive model of this "self-reflection" process based on Kayashima's two-layer working memory model, and developed a food recommender system using our cognitive model. In the test simulation, the users were satisfied with the foods that the system recommended, although the recommendation results were unexpected to the users. This implied the system practically worked to satisfy the user's expectation. On the other hand, the candidate recommendations which the system selected as its final output were different from those provided by the users. This suggests that the cognitive model needs improvement in terms of psychological reality.

    元の言語English
    ホスト出版物のタイトルHAI 2017 - Proceedings of the 5th International Conference on Human Agent Interaction
    出版者Association for Computing Machinery, Inc
    ページ517-521
    ページ数5
    ISBN(電子版)9781450351133
    DOI
    出版物ステータスPublished - 2017 10 17
    イベント5th International Conference on Human Agent Interaction, HAI 2017 - Bielefeld, Germany
    継続期間: 2017 10 172017 10 20

    Other

    Other5th International Conference on Human Agent Interaction, HAI 2017
    Germany
    Bielefeld
    期間17/10/1717/10/20

    ASJC Scopus subject areas

    • Human-Computer Interaction

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  • これを引用

    Tawatsuji, Y., Yasuda, Y., & Matsui, T. (2017). Construction of recommender system based on cognitive model for "self-reflection". : HAI 2017 - Proceedings of the 5th International Conference on Human Agent Interaction (pp. 517-521). Association for Computing Machinery, Inc. https://doi.org/10.1145/3125739.3132612