文章基本信息

标题：Improved BSP Clustering Algorithm for Social Network Analysis
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作者：Sanjiv Sharma ; R. K. Gupta
期刊名称：International Journal of Grid and Distributed Computing
印刷版ISSN：2005-4262
出版年度：2010
卷号：3
期号：3
出版社：SERSC
摘要：Social network analysis is a new research field in data mining. The clustering in social network analysis is different from traditional clustering. It requires grouping objects into classes based on their links as well as their attributes. While traditional clustering algorithms group objects only based on objects' similarity, and it can't be applied to social network analysis. So on the basis of BSP (business system planning) clustering algorithm, a social network clustering analysis algorithm is proposed. The proposed algorithm, different from traditional BSP clustering algorithms, can group objects in a social network into different classes based on their links and identify relation among classes dynamically & require less amount of memory
关键词：SNA; BSP; Link list; clustering algorithm; Data mining