We present here a recommending system that has been developed for filtering TV content provided to mobile devices users. This recommender is fully based on ontologies, which are used to formalize both the user and her/his interests, and the audiovisual content. The developed ontologies allow matchmaking between user and content at different levels, based on three means to define user interests: according to categories, content description, or any combination of concepts defined in an ontology. The computation of user profiles relies on both explicit and implicit profiling, based on incremental learning of interest degrees from content usage.
['Yannick Naudet', 'Armen Aghasaryan', 'Yann Toms', 'Christophe Senot']
An Ontology-Based Profiling and Recommending System for Mobile TV