Abstract:

Community detection is the key problem in studying complex network structure. An

overlapping community detection algorithm SAEC based on edges is proposed based on the

analysis of those existing means. The SAEC algorithm regards the community as a set of

edges, defines the edge similarity and obtains the transition probability matrix. Using

spectral clustering method, the number of communities is automatically determined by

calculating the eigenvalues and eigenvectors of the transition probability matrix. Then, the

overlapping community detection is completed by Kmeans algorithm. The effectiveness of the

algorithm is verified by randomly generated test networks and real networks.

Key words: network community;spectral cluster;edge;detection