Automatic determination of genre-specific relevance of recommendations in a social network

Abstract

The present invention relates to an operating method of operating a recommender system, a filtering apparatus () for a recommender system (), a recommender system and a corresponding computer program. An idea of the invention is to automatically learn for a user A in a social network, which recommendations of contacts of user A, who are also members of the social network, are relevant with respect to a genre into which user A is interested in. A learning algorithm is used to interpret feedback from user A in response to receiving recommendations from his/her contacts. Thereby, for each combination of a contact and a genre, a relevance-taste index can be determined. The determined relevance-taste index is subjected to a filter. Only such recommendations are provided to user A, whose associated relevance-taste indices fulfill a filtering criterion. Thereby, the amount of irrelevant recommendations submitted to user A can be significantly reduced.