计算机应用与软件Issue(12)：8-11,4.DOI:10.3969/j.issn.1000-386x.2013.12.003
基于边密度的复杂网络社区结构划分方法
PARTITION METHOD FOR COMMUNITY STRUCTURE IN COMPLEX NETWORKS BASED ON EDGE DENSITY
摘要
Abstract
The community structure detection algorithm based on optimal module degree will have the problems of resolution limit and high time complexity,etc.In light of this,we propose an edge density-based community structure detection algorithm .The algorithm can partition the network in regard to community structure but will not form the problem of resolution limit .The algorithm has the operation complexity of O( k· m) ,where m is the number of edges in the network and k is the maximum degree of node in the network .In order to verify the correctness and performance of the algorithm,we compare it with two of the famous community detection approaches ,namely GN and NF algorithms.Experi-ment results show that the proposed algorithm is feasible and effective .关键词
复杂网络/社区结构/分辨率限制/边密度/自动探测Key words
Complex networks/Community structure/Resolution limit/Edge density/Automatic detection分类
信息技术与安全科学引用本文复制引用
周林,晏立,沈项军..基于边密度的复杂网络社区结构划分方法[J].计算机应用与软件,2013,(12):8-11,4.基金项目
国家自然科学基金项目（61005017）；江苏省高校自然科学基金项目（10KJB520005）。 （）
