摘要
延续广泛应用的社团结构分级聚类方法,提出了衡量网络社团结构的社团稠密度概念,从而反映了网络结构整体性质的重要特征,并将参数应用于对网络社团聚类的研究当中.特别是基于社团稠密的四元结构提出了基于四元加权消减的社团划分算法.通过复杂网络实例验证了该算法的有效性,并对实验结果进行了比较分析,得出该算法在准确性方面对加权网络有较好效果.
Community structure is a common property that exists in complex networks. Improved divisive method is used in this paper in order to transform the communities detecting into weighted and reduced analysis problem. Then, this paper proposes a new concept of community density which measures community structure, and applies it to community structure demarcation. Especially, a new tetra-element weighted and reduced algorithm closely combined with community density is proposed. We also make the comparison and analysis of the experimental results and obtain a conclusion that the proposed new algorithm presents fitness in veracity for weighted networks.
出处
《延边大学学报(自然科学版)》
CAS
2009年第1期68-71,共4页
Journal of Yanbian University(Natural Science Edition)
关键词
社团结构
加权消减算法
社团稠密度
复杂网络
加权网络
community structure
weighted and reduced algorithm
community density
complex networks
weighted network