A Personalization Recommendation Method Based on Fuzzy Cluster
Lihong Jiang · Jisuanji gongcheng · 2006
This paper presents a new recommendation method,which combines the similar relation in attributes and characters of items to user-based collaborative filtering recommendation algorithm by fuzzy clustering algorithm.The method transforms the users' preferences of single item to similar groups,which forms the dense preferences of users-fuzzy cluster.Then this method predicts item ratings that users have not rated by the similarity of items in similar groups.Finally this method realizes the user-based collaborative filtering recommendation algorithm based on the above steps.The experimental results show that this method can provide better recommendation results than traditional user-based collaborative filtering recommendation algorithm.