Collaborative Filtering Algorithm Based on Fuzzy Clustering

To deal with the sparsity and expansibility of traditional collaborative filtering algorithm,which affects the accuracy of their recommendations,a collaborative filtering algorithm based on fuzzy cluster is proposed in this paper.It applies fuzzy clustering method to cluster the item,and computes the similarity between the users by analyzing the average ratings that the k users rate the items of the clusters.It predicts the ratings of the items that the k users rate based on the ratings of the neighbors that they rate,chooses the first n recommendations.Experimental result demonstrates that the algorithm can improve the accuracy of recommendation under the condition of the extreme sparsity of user rating data.