Matrix Factorization Recommendation Algorithm Based on Multiple Social Relationships

With the widespread use of social networks, recommendation algorithms that add relationships between users to recommender systems have been widely applied. Existing only introduced one type relationship system, but in reality, there are often multiple among users. In this paper, a new matrix factorization algorithm combined with is proposed. Through experiment results analysis on Epinions dataset, proposed has significant improvement over traditional and integrate single relationship.