Research on collaborative filtering algorithm of bipartite network oriented to personal recommendation system

In order to improve the recommendation efficiency and accuracy of personalized recommendation system,this paper presented a collaborative filtering algorithm based on bipartite network for personalized recommendation system.The collaborative filtering algorithm described personal recommendation system using bipartite network,and used grey relationship degree to measure user similarity and object similarity.It forecasted the object score of user evaluation with similarity-weighted of grey relationship degree,and then provided ordered object list to every user.Experimental results show that the collaborative filtering algorithm can effectively resolve above problems,and it is higher accuracy and reliability and better recommendation results.