Hybrid Recommender Systems: Survey and Experiments
User Modeling and User-Adapted Interaction
IEEE Transactions on Knowledge and Data Engineering
Semantic modelling using TV-anytime genre metadata
EuroITV'07 Proceedings of the 5th European conference on Interactive TV: a shared experience
AVATAR: an improved solution for personalized TV based on semantic inference
IEEE Transactions on Consumer Electronics
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In order to support the demands of fast and precise TV categorization for a personalized Electronic Programming Guide (EPG), the authors propose a new multidimensional taxonomy for the TV content. In addition to being much more lightweight in nature than the approach proposed by TV Anytime, with this method, a much more streamlined format is generated, which attempts to balance sensitive and detailed categorization criteria with computer efficiency in order to fulfill the demands of the recommender system. Furthermore, the authors propose a mechanism to obtain a quick and efficient real-time comparison of specific TV content with an alternative system called TV content fingerprinting