A Model of Social Explanations for a Conversational Movie Recommendation System

Pecune, F., Murali, S., Tsai, V., Matsuyama, Y. and Cassell, J. (2019) A Model of Social Explanations for a Conversational Movie Recommendation System. In: 7th International Conference on Human-Agent Interaction (HAI 2019), Kyoto, Japan, 06-10 Oct 2019, pp. 135-143. ISBN 9781450369220 (doi: 10.1145/3349537.3351899)

Abstract

A critical aspect of any recommendation process is explaining the reasoning behind each recommendation. These explanations can not only improve users' experiences, but also change their perception of the recommendation quality. This work describes our human-centered design for our conversational movie recommendation agent, which explains its decisions as humans would. After exploring and analyzing a corpus of dyadic interactions, we developed a computational model of explanations. We then incorporated this model in the architecture of a conversational agent and evaluated the resulting system via a user experiment. Our results show that social explanations can improve the perceived quality of both the system and the interaction, regardless of the intrinsic quality of the recommendations.

• Item Type: Conference Proceedings
• Additional Information: This work was supported in part by funding from Oath and the IT R&D program of MSIP/IITP [2017-0-00255, Autonomous digital companion development].
• Keywords: Conversational recommendation system, explanations, socially-aware.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Pecune, Mr Florian
• Authors: Pecune, F., Murali, S., Tsai, V., Matsuyama, Y., and Cassell, J.
• College/School: College of Medical Veterinary and Life Sciences > School of Psychology & Neuroscience
• ISBN: 9781450369220
• Copyright Holders: Copyright © 2019 Association for Computing Machinery
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher

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