A new community detection method based on coupled map lattice model

摘要

This paper proposes a novel algorithm to detect the community structure. Based on cascading failure model, the algorithm reveals the relationship between network nodes. Then, we exploited the k-nearest neighbors algorithm to transform the relationship between the nodes into European space, and quantitatively describe the close relationship between the nodes. Consequently, the network nodes will be clustered and we can get different network community divisions. In all possible community divisions, the one with the maximum modularity is the optimal community structure for the algorithm. Experiments on several benchmark networks are presented and the results show the effectiveness and reliability of our algorithm.