计算机技术与发展2016，Vol.26Issue(4)：51-55,5.DOI:10.3969/j.issn.1673-629X.2016.04.011
基于Weighted-slope One的用户聚类推荐算法研究
Research on User Clustering Recommendation Algorithm Based on Weighted-slope One
摘要
Abstract
Aiming at the problems of data sparseness and the poor real-time performance of traditional collaborative filtering recommenda-tion algorithm,a new user clustering recommendation algorithm based on Weighted-slope One algorithm is proposed. Firstly,the zero i-tems in user-item matrix are filled by Weighted-slope One algorithm. This operation can effectively reduce the data sparseness. Second-ly,the users are clustered by the optimized K-means algorithm. This operation can effectively find the nearest neighbor of the target user. Finally,the corresponding products are recommended to the target users according to their nearest neighbors which are found by the us-ers’ collaborative filtering recommendation algorithm. Experimental results show that the improved algorithm can significantly reduce the data sparseness,and improve the real time performance and the accuracy of recommendation.关键词
协同过滤/高维稀疏矩阵/Weighted-slope One/K -means/聚类中心Key words
collaborative filtering/high-dimensional sparse matrix/Weighted-slope One/K -means/clustering center分类
信息技术与安全科学引用本文复制引用
郑丹,王名扬,陈广胜..基于Weighted-slope One的用户聚类推荐算法研究[J].计算机技术与发展,2016,26(4):51-55,5.基金项目
中央高校基本科研业务费专项资金项目(2572014DB05) （2572014DB05）
中国博士后科学基金面上基金(2012M520711) （2012M520711）
国家自然科学基金资助项目(71473034) （71473034）
