The Design and Implementation of Composite Collaborative Filtering Algorithm for Personalized Recommendation
The Design and Implementation of Composite Collaborative Filtering Algorithm for Personalized Recommendation
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DOI：
10.4304/jsw.7.9.2040-2045
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发表时间：
2012-01
期刊：
影响因子：
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通讯作者：
Liang Hu;Wenbo Wang;Feng Wang;Xiaolu Zhang;Kuo Zhao
中科院分区：
文献类型：
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作者：
Liang Hu;Wenbo Wang;Feng Wang;Xiaolu Zhang;Kuo Zhao
针对原有协同过滤算法存在的“无用户启动“和“数据稀疏”等问题，提出了一种基于斯皮尔曼等级相关系数的复合协同过滤个性化推荐算法。本文将采用Top-M推荐算法来得到最终的结果。最后通过实例验证了该算法比基于用户的协同过滤算法和基于项目的协同过滤算法具有上级的优越性。
A composite collaborative filtering algorithm for personalized recommend will be presented to solve the original Collaborative Filtering algorithm problem including“None of User Starting ”and “Data Sparsity”, and the Spearman rank correlation coefficient will be used as a main correlation coefficient. Top-M commended is going to be used to get the final results in this paper. At last, we will validate that this algorithm is superior to the algorithm of collaborative filtering based on user and the algorithm of collaborative filtering based on item.