A Hybrid Recommender System Combining Collaborative Filtering with Neural Network

We propose a new recommender system which combines collaborative filtering(CF) with Self-Organizing Map(SOM) neural network. First, all users are segmented by demographic characteristics and users in each segment are clustered according to the preference of items using the SOM neural network. To recommend items to a user, CF algorithm is then applied on the cluster where the user belongs. As a result of experimentation for well-known movies, we show that the proposed system satisfies the predictability of CF algorithm in GroupLens. Also, our system improves the scalability and the performance of the traditional CF technique.