Abstract: The two recommender systems which arc respectively based on content and collaborative filtering methods are most popular. Both types of filtering methods have advantages and disadvantages. This paper proposed a new isomorphic integrated model and algorithm which have the merits of the traditional recommender systems based on above two methods, and avoid the shortages of them to some extent. The experimental results show that the presented isomorphic integrated model and algorithm can improve the performance of the traditional recommender systems in predictive accuracy.

Key words: Isomorphic integrated, Content based, Collaborative filtering, Recommender system model