面向复杂有权网络的社区发现方法研究

复杂网络中节点之间的连接强度会在很大程度上影响网络的社区结构,利用权重来刻画连接强度的差异性,并将其应用到社区发现研究中具有重要的意义。针对目前有权网络的社区发现方法存在的不足,该文结合节点的直接连边权重和基于共同邻居节点的连边权重,提出了一种改进的节点相关度度量准则。进一步基于这种改进的节点相关度度量准则和团体之间的聚集方法,构建了面向有权网络的社区发现模型。分别在有权值的科学家合作网络和全国列车网络数据集上进行了社区发现实验,结果表明了方法的有效性。

Research on Community Detection from Complex Weighted Network

The connection strength between nodes in complex networks can largely affect the community structure of the network, therefore, it is of great significance to use the weight to describe the difference of the connection strength and apply it to the community discovery research. For this purpose, this paper proposes an improved method for measuring the correlation degree of nodes based on the direct link weights of nodes and the edge weights of common neighbor nodes. Furthermore, we construct a community discovery model based on the improved measure of the correlation degree between nodes and the aggregation method between groups. The experiments are performed on the weighted network of scientists and the national train network, and the results show the effectiveness of this method.