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Construction of Recommender System based on Cognitive Model for "Self-Reflection"

Published:27 October 2017Publication History

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.

References

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  1. Construction of Recommender System based on Cognitive Model for "Self-Reflection"

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      cover image ACM Conferences
      HAI '17: Proceedings of the 5th International Conference on Human Agent Interaction
      October 2017
      550 pages
      ISBN:9781450351133
      DOI:10.1145/3125739

      Copyright © 2017 ACM

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      Publication History

      • Published: 27 October 2017

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