A Community-Based Recommendation System to Reveal Unexpected Interests

Current collaborative filtering can't represent various aspects of users' interests. We propose a recommendation method in which a user can find new interests that are partially similar to the user's taste. Partial similarity is an aspect of the user's preference which is projected by the community in which the user belongs. We developed a television program recommendation system which performs such recommendation with serendipity, conducted an actual experiment and evaluated its results.