Experiments with a Recommendation Technique that Learns Category Interests

An important step in providing personalized information is predicting the level of interest in information for a specific user. This paper describes a technique that predicts this level of interest for information that is described by a set of categories. The technique is tested in a movie recommendation system and compared with the social filtering prediction technique. The results show that the category-based prediction technique outperforms social filtering.