A New Community Structure Detection Method Based on Structural Similarity

Abstract

Community structure detection is to use the graph topology, which means the community structure, is analyzed from the complex network. It is very important to understand and use the network structure. Recently, a lot of algorithms are presented to search the community structure of the complex network. In combination with the structural similarity and local modularity measure, this paper proposed a new structure-based similarity community structure discovery method (SSCSD). The basic idea is, with the local modularity as criteria, based on structural similarity between the vertices and using the node's local information efficiently to find the community structure of complex networks. Experimental results show that the method can be better for many network division results.