Amazon.com Recommendations: Item-to-Item Collaborative Filtering
IEEE Internet Computing
METIORE: A Personalized Information Retrieval System
UM '01 Proceedings of the 8th International Conference on User Modeling 2001
tagging, communities, vocabulary, evolution
CSCW '06 Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work
AVATAR: an improved solution for personalized TV based on semantic inference
IEEE Transactions on Consumer Electronics
Information Sciences: an International Journal
Viewer behaviors and practices in the (new) television environment
Proceedings of the 11th european conference on Interactive TV and video
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This paper presents the methods used in a TV Recommender System that helps users in the difficult task of finding an interesting TV program from among the hundreds of channels that we can find nowadays on TV. Our aim is to cover not only user preferences but also user restrictions while watching TV. The recommendations use a hybrid method, combining content based and folksonomy (collaborative and social recommendations). We also present interesting initial results of some experiments that try to show the accuracy of the users recommendations.