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浙江大学学报(工学版)
J4  2013, Vol. 47 Issue (4): 656-661    DOI: 10.3785/j.issn.1008-973X.2013.04.014
    
Community clustering model for E-commerce trust based on social network
ZHANG Shao-zhong, FANG Zhao-xi, CHEN Jun-gan, SHI Jiong
Institute of Electronics and Information, Zhejiang Wanli University, Ningbo 315100, China
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Abstract  

A method of social network analysis was used to establish a trust community clustering model for E-commerce and discuss the building of trust network. Then the analysis of trust community clustering was conducted. The trust information degree was established based on mutual information theory. Direct trust information degree and global trust information degree were adopted to build trust relations among subjects. Trust community clustering was used to represent the most trust relationship network for users. Clustering coefficient and global trust information degree were adopted to construct trust community clustering, and a clustering algorithm was presented. Experimental results show that the model of trust community clustering can well describe the trust relationship and the algorithm has obvious advantages in accuracy and time cost.

Published: 01 April 2013
CLC:  ＴＰ ３１９  
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Cite this article:

ZHANG Shao-zhong, FANG Zhao-xi, CHEN Jun-gan, SHI Jiong. Community clustering model for E-commerce trust based on social network. J4, 2013, 47(4): 656-661.

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http://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2013.04.014     OR     http://www.zjujournals.com/eng/Y2013/V47/I4/656


基于社会网络的电子商务信任社区聚类模型

采用社会网络分析的方法建立电子商务信任社区聚类模型,讨论信任网络构建问题,进行信任网络社区聚类分析.通过互信息方法构建信任信息度,采用直接信任信息度和全局信任信息度描述主体之间的信任程度.提出使用信任社区聚类的方法分析用户最信任的网络关系,采用聚类系数和全局信任信息度进行信任社区聚类分析,给出电子商务信任社区聚类优化算法.实验表明,利用该方法构建的信任社区聚类模型能够反映电子商务主体间接的信任关系,与现有的其他方法相比,该模型具有较高的精确度.

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