A hybrid recommendation algorithm based on social networks

Abstract

In the light of the problem of collaborative recommendation and content-based cold start, this paper proposes a hybrid recommendation system based on social network. The method is based on the user social relations network. According to the social behavior of user, by establishing the model of social network users, it puts forward the user similarity measure. Then it takes random walk algorithm as a basis and selects out N users who have the highest similarity with the users' interest. The test results show that this method can obtain better recommendation effect and customer satisfaction.