基于结构和适应度的社区发现

Community detection based on structure and fitness

复杂社会网络无处不在,对复杂社会网络进行社区发现越来越被人们重视.基于局部结构的社区发现可以在不用了解全局的情况下对某些节点进行划分;社会网络的社区适应度特性可以找出不同适应度下的社区结构.基于局部结构以及社区适应度的网络属性,提出一种新的社区发现算法.通过实验比较,算法能较好、较快的发现社区结构,在人工网络以及真实社会网络均取得较之已有方法更好的效果.

Many systems can be described as complex social networks ,and increasing attention has been paid to the detection of social communities out of complex social networks .Structured-based community detection can be achieved locally without knowledge of the overall situation . The community fitness characteristics of social networks can help to identify community structures at different fitnesses .A new algorithm based on structure and fitness was proposed to test large generated networks and real networks . Experiments had show n its better efficiency and higher accuracy .