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An Improved Item-based Collaborative Filtering Algorithm Based on Compound Weighted Rating |
Ma Li |
(Business College, China West Normal University, Nanchong 637002, China) |
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Abstract In view of the problem that recommendation quality is seriously influenced by the sparsity of user ratings,an improved Item-based collaborative filtering algorithm based on compound weighted rating is proposed. The union of user rating items is used as the basis of similarity computing among items, moreover a compound weighted rating method is proposed to compute and complete the missing values in the union of user rating items for decreasing the sparsity. The experimental results show that the new algorithm can efficiently improve recommendation quality.
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Received: 05 August 2008
Published: 25 November 2008
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Corresponding Authors:
Ma Li
E-mail: cnmali@yahoo.cn
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About author:: Ma Li |
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