Community detection algorithm based on signal adaptive transmission
TAN Chunni1, ZHANG Yumei2, ZHANG Jiatong3, WU Xiaojun1,2
1. School of Physics and Information Technology, Shaanxi Normal University, Xi'an Shaanxi 710119, China;
2. School of Computer Science, Shaanxi Normal University, Xi'an Shaanxi 710119, China;
3. School of Cultural Heritage, Northwest University, Xi'an Shaanxi 710127, China
In order to accurately detect the community structure of complex networks, a community detection algorithm based on signal adaptive transmission was proposed. First, the signal was adaptively passed on complex networks,thereby getting the vector affecting on the entire network of each node, then the topological structure of each node was translated into geometrical relationships of algebra vector space. Thus, according to the nature of the clustering, the community structure of the network was detected. In order to get the feasible spatial vectors, the optimum transfer number was determined, which reduced the searching space, and effectively strengthened the search capability of community detection.The proposed algorithm was tested on computer-generated network, Zachary network and American college football network. Compared with Girvan-Newman (GN) algorithm, spectral clustering algorithm,extremal optimization algorithm and signal transmission algorithm, the results show that the accuracy and precision of the proposed community division algorithm is feasible and effective.
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2015, Vol. 35 
