Recommender systems are a type of systems that recommend interest items to users. A widely used recommendation technique in recommender systems is collaborative filtering. In this technique, we assume that users, who share the preferences on some items, share these preferences on the other items. Clustering methods can be used for collaborative filtering technique. In this paper a new hybrid clustering method is presented to improve the recommender system results. The proposed method utilizes both user profiles and user-item rating matrix as its information sources. Moreover, a new heuristic method is presented to ensemble clusters. K-means method is used as the clustering method. Then, the set of items will be recommended to the new user based of its detected ensemble cluster. The results of experiments on movie lens dataset show that the proposed method enhances the efficiency of recommender systems.
کلید واژگان :Recommender system, Collaborative filtering, Clustering, Recommending, K-means
ارزش ریالی : 300000 ریال
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