一种基于社团结构的局域复杂网络模型

Local Complex Network Model Based on Community Structure

BA模型用增长和优先连接两个机制解释了复杂网络的基本特性幂律分布,局域世界模型通过注意到优先连接是限制性的而进行了进一步的发展,本文认为局域世界模型中局部集团中的节点事实上是有着密切关系的,因而在新节点加入时采用GNM算法进行社团分解产生局部集团,提出基于社团分解的局域复杂网络模型(CLW模型).我们进行的理论分析和实验模拟表明,CLW模型具有小的网络平均最短路径,同时它的平均聚类系数要远大于局域世界模型,更接近于真实的复杂网络.

The BA model explain the power-law distribution of the complex network by using the method of the growth and preferential attachment,and the local-world evolving network makes a new progress by finding that the preferential attachment is restrictive. This paper has an idea that the nodes of the local group in the local-world evolving network have intimate relationship in fact so that bring the local group forth decomposing the communities using the GNM algorithm while the new node adding. And it raise the local complex network based on the community structure. The theory analysis and experiment simulation make clear that the CLW model have both the little network average shortest path and that its network average clustering coefficient is bigger than the local-world evolving network model,which is approaching the true complex network.