A novel fuzzy recommendation system integrated the experts´ opinion

Collaborative Filtering (CF) has been applied to many commercial systems successfully, such as IMDB, Netflix and son on. The basic idea of a CF system is to generate recommendations based on the experiences of past similar users. The users´ option can be categorized into objective and subject information. The former was furnished by the common users and the later represents solicit opinions provided by experts (such as film critics). Both information types are valuable and important for the CF system. This study attempts to propose a novel collaborative filtering framework based on fuzzy set theory which integrates the subjective and objective information. The new methodology not only provides a comprehensive result but also solve the problems of traditional CF system, new user and new item. Finally, an experiment is performed, and the result indicates that the proposed methodology produces high-quality recommendations.