Integrating facial expressions into user profiling for the improvement of a multimodal recommender system

Authors:
Ioannis Arapakis;Yashar Moshfeghi;Hideo Joho;Reede Ren;David Hannah;Joemon M. Jose
Affiliations:
Department of Computing Science, University of Glasgow, Glasgow;Department of Computing Science, University of Glasgow, Glasgow;Department of Computing Science, University of Glasgow, Glasgow;Department of Computing Science, University of Glasgow, Glasgow;Department of Computing Science, University of Glasgow, Glasgow;Department of Computing Science, University of Glasgow, Glasgow
Venue:
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Year:
2009

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Abstract

Over the years, recommender systems have been systematically applied in both industry and academia to assist users in dealing with information overload. One of the factors that determine the performance of a recommender system is user feedback, which has been traditionally communicated through the application of explicit and implicit feedback techniques. In this paper, we propose a novel video search interface that predicts the topical relevance of a video by analysing affective aspects of user behaviour. We, furthermore, present a method for incorporating such affective features into user profiling, to facilitate the generation of meaningful recommendations, of unseen videos. Our experiment shows that multimodal interaction feature is a promising way to improve the performance of recommendation.