Information entropy based multi-criteria recommendation

In recent years, many e-commerce sites allow users to evaluate multiple aspects of a product, which provides a more comprehensive user preference information for the recommendation system and helps improve the recommendation quality. Therefore, multi-criteria recommender systems have increasingly attracted researchers' interest in recent years. In this paper, we propose an information entropy based multi-criteria recommendation algorithm. The results from experiments based on Yahoo Movie dataset show that the new method can improve the recommendation accuracy of recommender systems.