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

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    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.

    Original languageEnglish
    Title of host publicationHAI 2017 - Proceedings of the 5th International Conference on Human Agent Interaction
    PublisherAssociation for Computing Machinery, Inc
    Pages517-521
    Number of pages5
    ISBN (Electronic)9781450351133
    DOIs
    Publication statusPublished - 2017 Oct 17
    Event5th International Conference on Human Agent Interaction, HAI 2017 - Bielefeld, Germany
    Duration: 2017 Oct 172017 Oct 20

    Other

    Other5th International Conference on Human Agent Interaction, HAI 2017
    CountryGermany
    CityBielefeld
    Period17/10/1717/10/20

    Fingerprint

    Recommender systems
    Data storage equipment

    Keywords

    • Cognitive model
    • Meta-cognition
    • Recommender system
    • Self-reflection

    ASJC Scopus subject areas

    • Human-Computer Interaction

    Cite this

    Tawatsuji, Y., Yasuda, Y., & Matsui, T. (2017). Construction of recommender system based on cognitive model for "self-reflection". In 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

    Construction of recommender system based on cognitive model for "self-reflection". / Tawatsuji, Yoshimasa; Yasuda, Yuki; Matsui, Tatsunori.

    HAI 2017 - Proceedings of the 5th International Conference on Human Agent Interaction. Association for Computing Machinery, Inc, 2017. p. 517-521.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Tawatsuji, Y, Yasuda, Y & Matsui, T 2017, Construction of recommender system based on cognitive model for "self-reflection". in HAI 2017 - Proceedings of the 5th International Conference on Human Agent Interaction. Association for Computing Machinery, Inc, pp. 517-521, 5th International Conference on Human Agent Interaction, HAI 2017, Bielefeld, Germany, 17/10/17. https://doi.org/10.1145/3125739.3132612
    Tawatsuji Y, Yasuda Y, Matsui T. Construction of recommender system based on cognitive model for "self-reflection". In HAI 2017 - Proceedings of the 5th International Conference on Human Agent Interaction. Association for Computing Machinery, Inc. 2017. p. 517-521 https://doi.org/10.1145/3125739.3132612
    Tawatsuji, Yoshimasa ; Yasuda, Yuki ; Matsui, Tatsunori. / Construction of recommender system based on cognitive model for "self-reflection". HAI 2017 - Proceedings of the 5th International Conference on Human Agent Interaction. Association for Computing Machinery, Inc, 2017. pp. 517-521
    @inproceedings{40e3de2d0ba943fcb72c0598ef1b72ee,
    title = "Construction of recommender system based on cognitive model for {"}self-reflection{"}",
    abstract = "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.",
    keywords = "Cognitive model, Meta-cognition, Recommender system, Self-reflection",
    author = "Yoshimasa Tawatsuji and Yuki Yasuda and Tatsunori Matsui",
    year = "2017",
    month = "10",
    day = "17",
    doi = "10.1145/3125739.3132612",
    language = "English",
    pages = "517--521",
    booktitle = "HAI 2017 - Proceedings of the 5th International Conference on Human Agent Interaction",
    publisher = "Association for Computing Machinery, Inc",

    }

    TY - GEN

    T1 - Construction of recommender system based on cognitive model for "self-reflection"

    AU - Tawatsuji, Yoshimasa

    AU - Yasuda, Yuki

    AU - Matsui, Tatsunori

    PY - 2017/10/17

    Y1 - 2017/10/17

    N2 - 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.

    AB - 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.

    KW - Cognitive model

    KW - Meta-cognition

    KW - Recommender system

    KW - Self-reflection

    UR - http://www.scopus.com/inward/record.url?scp=85034836003&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=85034836003&partnerID=8YFLogxK

    U2 - 10.1145/3125739.3132612

    DO - 10.1145/3125739.3132612

    M3 - Conference contribution

    SP - 517

    EP - 521

    BT - HAI 2017 - Proceedings of the 5th International Conference on Human Agent Interaction

    PB - Association for Computing Machinery, Inc

    ER -