An Overlapped Community Partition Algorithm Based on Line Graph

Overlapped communities detection in complex networks is one of the most intensively investigated problems in recent years. In order to accurately detect the overlapped communities in these networks, an algorithm using edge features, namely SAEC, is proposed. The algorithm transforms topology graph of nodes into line graph of edges and calculates the similarity matrix between nodes, then the edges are clustered using spectral analysis, thus we classify the edges into corresponding communities. According to the attached communities of edges, we cluster the nodes incident with the edges again to find the overlapped nodes among the communities. Experiments on randomly generated and real networks validate the algorithm.

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