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Acquiring Personal Attributes Using Communication Robots for Recommendation System

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Intelligent Robotics and Applications (ICIRA 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9835))

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Abstract

It looks easy to continue conversations and make them fun, but it is difficult because of various factors. It is difficult to continue conversations with the common topics. Conversations aren’t continued without pleasant topics. If pleasant topics are obtained from personal attributes, conversations become lively and he/she wants to talk about himself/herself. It is difficult to obtain pleasant topics from personal attributes. If robots research and analyze about them daily, personal attributes are obtained effectively. This paper describes dialog system to obtain personal attributes and recommend information based on personal attributes.

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Authors and Affiliations

  1. Faculty of System Design, Tokyo Metropolitan University, Tokyo, Japan

    Aoi Suzuki, Eri Sato-Shimokawara, Toru Yamaguchi & Kentaro Ikehata

Authors
  1. Aoi Suzuki
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  2. Eri Sato-Shimokawara
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  3. Toru Yamaguchi
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  4. Kentaro Ikehata
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Corresponding author

Correspondence to Aoi Suzuki .

Editor information

Editors and Affiliations

  1. Tokyo Metropolitan University , Tokyo, Japan

    Naoyuki Kubota

  2. Kyushu University , Fukuoka, Japan

    Kazuo Kiguchi

  3. University of Portsmouth , Portsmouth, United Kingdom

    Honghai Liu

  4. Tokyo Metropolitan University , Tokyo, Japan

    Takenori Obo

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© 2016 Springer International Publishing Switzerland

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Suzuki, A., Sato-Shimokawara, E., Yamaguchi, T., Ikehata, K. (2016). Acquiring Personal Attributes Using Communication Robots for Recommendation System. In: Kubota, N., Kiguchi, K., Liu, H., Obo, T. (eds) Intelligent Robotics and Applications. ICIRA 2016. Lecture Notes in Computer Science(), vol 9835. Springer, Cham. https://doi.org/10.1007/978-3-319-43518-3_23

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  • DOI: https://doi.org/10.1007/978-3-319-43518-3_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-43517-6

  • Online ISBN: 978-3-319-43518-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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