Recommendation for Movies and Stars Using YAGO and IMDB

With the rapid growth of web data, people sometime need semantic similar information in order to obtain a clear outline of their interests, so recommendation is needed to provide relevant information to users' queries. In this paper, we propose a method to recommend semantic similar movies and stars to users' queries, styles and stories. The system measures the similarities between movies according to genre and style features extracted from YAGO and IMDB. Experimental results show that the recommendations meet users' interests.