Authors
Ioannis Arapakis, Yashar Moshfeghi, Hideo Joho, Reede Ren, David Hannah, Joemon M Jose
Publication date
2009/6/28
Conference
2009 IEEE International Conference on Multimedia and Expo
Pages
1440-1443
Publisher
IEEE
Description
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.
Total citations
Scholar articles
I Arapakis, Y Moshfeghi, H Joho, R Ren, D Hannah… - 2009 IEEE International Conference on Multimedia and …, 2009