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Authors: Dai Yodogawa 1 and Kazuhiro Kuwabara 2

Affiliations: 1 Graduate School of Information Science and Engineering, Ritsumeikan University, Kusatsu, Shiga 525-8577 Japan ; 2 College of Information Science and Engineering, Ritsumeikan University, Kusatsu, Shiga 525-8577 Japan

ISBN: 978-989-758-395-7

ISSN: 2184-433X

Keyword(s): Group Recommender System, User Model, Agent, Conversation Strategy.

Abstract: For a group recommender system, it is important to recommend an item that can be accepted by all group members. This paper proposes a group recommender system where preferences elicited from group members are used to select an item that is agreeable to all of them. In this system, an agent that corresponds to each group member manages estimation of the corresponding user’s preferences. Virtual negotiation is conducted among these agents to find an appropriate item to recommend, and the selected item is presented to group members. If it is not accepted, the system asks members to relax their requirements and accordingly updates its recommendation. We report and discuss the results of simulation experiments with different personality types of conflict resolution and different conversation strategies.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Yodogawa, D. and Kuwabara, K. (2020). Reaching Agreement in an Interactive Group Recommender System. In Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-395-7 ISSN 2184-433X, pages 295-302. DOI: 10.5220/0009160502950302

@conference{icaart20,
author={Dai Yodogawa. and Kazuhiro Kuwabara.},
title={Reaching Agreement in an Interactive Group Recommender System},
booktitle={Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2020},
pages={295-302},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009160502950302},
isbn={978-989-758-395-7},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Reaching Agreement in an Interactive Group Recommender System
SN - 978-989-758-395-7
IS - 2184-433X
AU - Yodogawa, D.
AU - Kuwabara, K.
PY - 2020
SP - 295
EP - 302
DO - 10.5220/0009160502950302

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