Collaborative Filtering Recommendation Based on Fuzzy Clustering in Personalization Services
Songjie Gong · Computer Engineering and Science · 2009
Recommendation system is one of the most important techniques for personalization services.Collaborative filtering is applied for building personalization recommendation systems.The efficiency of this method declines linearly with the number of users and items,and the failure of ensuring real-time requirements.A collaborative filtering method based on fuzzy clustering is proposed in this paper to solve this problem.Items are clustered based on users' ratings on items.Based on the similarity,the nearest neighbors of the target item can be found.The experimental results indicate that this method can effectively improve the real-time performance of recommendation systems.