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.
马丽. 基于组合加权评分的Item-based协同过滤算法[J]. 现代图书情报技术, 2008, 24(11): 60-64.
Ma Li. An Improved Item-based Collaborative Filtering Algorithm Based on Compound Weighted Rating. New Technology of Library and Information Service, 2008, 24(11): 60-64.
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