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Collaborative filtering algorithm incorporated with cluster-based expert selection

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成果类型:
期刊论文
作者:
Kong, Weiliang;Liu, Qingtang;Yang, Zhongkai;Han, Shuyun
通讯作者:
Kong, W.(byta100@yahoo.cn)
作者机构:
[Kong, Weiliang; Han, Shuyun; Yang, Zhongkai; Liu, Qingtang] National Engineering Research Center for Elearning, Central China Normal University, Wuhan 430079, China
通讯机构:
National Engineering Research Center for Elearning, Central China Normal University, China
语种:
英文
关键词:
Clustering;Collaborative filtering;Expert selection;Expert-based collaborative filtering;Similarity measure
期刊:
The Journal of Information and Computational Science
ISSN:
1548-7741
年:
2012
卷:
9
期:
12
页码:
3421-3429
机构署名:
本校为第一且通讯机构
院系归属:
教育信息技术学院
摘要:
In order to solve the scalability and the noise problems suffered by collaborative filtering algorithm, the researchers have proposed expert-based collaborative filtering algorithm. But, there still lacks a principled model for guiding how to select the useful experts. In this paper, firstly, we define a concept of expert which can be reduced into two components: the activity and the influence in a given domain. Secondly, we put forward cluster-based expert selection method. Thirdly, we introduce this method into expert-based collaborative filtering algorithm and propose collaborative filterin...

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