Javier G. Recuenco

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The authors present a possible approach for a new general purpose recommender architecture, one which complements the current proven and tested techniques (User Model, Collaborative Filtering, Content Based Filtering), used in some everyday business scenarios, balancing with newly developed personalization procedures and methodologies. The overall objective(More)
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(More)
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