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With the development of personalized recommendation systems, the research of collaborative filtering reached a bottleneck. Neither algorithm accuracy nor computational complexity can be improved significantly. In this paper, we present our statistics and analysis on some recognized datasets. The analysis shows that the real rating features of the users cannot follow even distribution while most current...
Personalized recommendation systems are becoming increasingly popular with the evolution of the Internet, and collaborative filtering is one of the most important technologies in recommender systems. Such technology recommends items to a customer according to the preference data of similar customers. The main problems of collaborative filtering are about prediction accuracy and data sparsity. To solve...
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