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

Yoshimasa Tawatsuji; Yuki Yasuda; Tatsunori Matsui

doi:10.1145/3125739.3132612

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

Yoshimasa Tawatsuji, Yuki Yasuda, Tatsunori Matsui

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	HAI 2017 - Proceedings of the 5th International Conference on Human Agent Interaction
Publisher	Association for Computing Machinery, Inc
Pages	517-521
Number of pages	5
ISBN (Electronic)	9781450351133
DOIs	https://doi.org/10.1145/3125739.3132612
Publication status	Published - 2017 Oct 17
Event	5th International Conference on Human Agent Interaction, HAI 2017 - Bielefeld, Germany Duration: 2017 Oct 17 → 2017 Oct 20

Other

Other	5th International Conference on Human Agent Interaction, HAI 2017
Country/Territory	Germany
City	Bielefeld
Period	17/10/17 → 17/10/20

Keywords

Cognitive model
Meta-cognition
Recommender system
Self-reflection

ASJC Scopus subject areas

Human-Computer Interaction

Access to Document

10.1145/3125739.3132612

Cite this

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 proceeding › Conference 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

@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 = oct,

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",

note = "5th International Conference on Human Agent Interaction, HAI 2017 ; Conference date: 17-10-2017 Through 20-10-2017",

}

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

AN - SCOPUS:85034836003

SP - 517

EP - 521

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

PB - Association for Computing Machinery, Inc

T2 - 5th International Conference on Human Agent Interaction, HAI 2017

Y2 - 17 October 2017 through 20 October 2017

ER -

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

Abstract

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this