[1]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(04):51-55.
　ZHENG Dan,WANG Ming-yang,CHEN Guang-sheng. Research on User Clustering Recommendation Algorithm Based on Weighted-slope One[J].,2016,26(04):51-55.
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 基于Weighted-slope One的用户聚类推荐算法研究()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
26
期数:
2016年04期
页码:
51-55
栏目:
智能、算法、系统工程
出版日期:
2016-04-10

文章信息/Info

Title:
 Research on User Clustering Recommendation Algorithm Based on Weighted-slope One
文章编号:
1673-629X（2016)04-0051-05
作者:
 郑丹; 王名扬; 陈广胜
 东北林业大学 信息与计算机工程学院
Author(s):
 ZHENG Dan; WANG Ming-yang; CHEN Guang-sheng
关键词:
 ; 协同过滤; 高维稀疏矩阵; Weighted-slope One ; K -means ; 聚类中心
Keywords:
 ; collaborative filtering; high-dimensional sparse matrix; Weighted-slope One; K -means; clustering center
分类号:
TP311
文献标志码:
A
摘要:
 针对传统协同过滤推荐算法存在的数据稀疏性以及实时性差的问题，提出一种基于Weighted-slope One的用户聚类推荐算法。该算法首先利用Weighted-slope One算法的思想对初始的用户-评分矩阵进行有效填充，降低数据的稀疏性；然后，结合初始聚类中心优化改进的K -means方法对用户进行聚类，生成相似用户集合，以缩小目标用户搜索最近邻的范围；最后，结合目标用户所属的聚类，利用基于用户的协同过滤算法搜索最近邻居，为目标用户推荐对应的产品。仿真实验结果表明，改进算法可以显著降低数据的稀疏度，同时提升推荐的准确性和实时性。
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.

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更新日期/Last Update: 2016-06-16