recommenders
A method and apparatus are disclosed for updating a user profile in a recommendation system for a given user based on auditory or gestural feedback information provided by the user. The auditory or gestural feedback is detected using audio or video processing techniques, or both, and includes, for example, auditory or gestural commands or facial expressions indicating the strength of the user's preferences. The auditory or gestural feedback can be explicit or implicit. Once predefined behavioral feedback is identified, the present invention updates the corresponding user profile, in an appropriate manner.
A television programming recommender is disclosed that generates television program recommendations based on a combined implicit/explicit program recommendation score. The disclosed television programming recommender combines the explicit viewing preferences of viewers with their television viewing behavior (implicit preferences) to generate program recommendations. Explicit viewing preferences can be obtained by having viewers rate their preferences for various program attributes. The explicit viewing preferences are then utilized to generate an explicit recommendation score, E, for an upcoming television program. Implicit viewing preferences can be obtained by monitoring a user's viewing history and analyzing the programs that are actually watched by a user (positive examples) and the shows that are not watched by the user (negative examples). The implicit viewing preferences are then utilized to generate an implicit recommendation score, I, for an upcoming television program. A combined recommendation score, C, is computed based on the explicit and implicit scores, E and I. In one implementation, the combined recommendation score, C, can be computed using a weighted linear mapping.
(C) Æliens 27/08/2009
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