计算机技术与发展Issue(10)：119-122,4.DOI:10.3969/j.issn.1673-629X.2015.10.026
一种基于聚类的社团划分算法
A Clustering-based Community Division Algorithm
摘要
Abstract
Community division has been a research focus in the social network area. In order to quickly and accurately find community structure in the social network,from the importance of nodes and consulting their similarities,propose a clustering-based community divi-sion algorithm CCDA. The basic idea of this algorithm is selecting the node owning greater clustering coefficient as the clustering center, calculating similarity by the shortest path and Euclidean distance,putting the node with similarity greater than given threshold to cluster, and iterating the process until the node collection is empty. For the repeated division nodes,the algorithm divides each of them into the most appropriate community by using the module function Q. The clusters generated by the algorithm are corresponding with the commu-nities. Since the algorithm starts from the important node and does not consider those clustered nodes when determining new clustering center,the time complexity of it is lower than GN algorithm and Newman algorithm. The results of applying the algorithm to the classical social network,the Zachary network,show that CCDA is valid in community division.关键词
社会网络/社团划分/聚集系数/相似性/聚类Key words
social network/community division/clustering coefficient/similarity/clustering分类
信息技术与安全科学引用本文复制引用
王伟,李玲娟..一种基于聚类的社团划分算法[J].计算机技术与发展,2015,(10):119-122,4.基金项目
国家“973”重点基础研究发展计划项目(2011CB302903) （2011CB302903）
