Affiliations: [a] Hebi Automotive Engineering Professional College, Hebi Vocational Education Park, Hebi, Henan 458030, China | [b] State Grid Corporation of China, Xinzheng, Henan 451100, China | [c] Institute of Matheatics and Information Technology, Jiaxing College, Jiaxing, Zhejiang 314000, China
Correspondence:
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Corresponding author: Yiran Li, State Grid Corporation of China, Xinzheng, Henan 451100, China. E-mail: [email protected].
Abstract: Community detection is an important way to describe the evolution of network events. In order to study.how to differentiate network community structure accurately and effectively, and solve the problem of the Sync clustering algorithm directly connected nodes without common neighbor nodes existing similarity underestimated tendency, and the synchronization time being too long, we put forward a method which breaks edge disconnection between connected nodes directly and add auxiliary nodes. We can think that the two nodes are connected by the secondary node and the edge of the two nodes connected respectively, and then realize the improvement of node similarity. Secondly this paper uses neighborhood radius to divide community, and detect the community before the node object has reacded fully synchronous. Simulation experiments are done respectively on the artificial data and real data sets generated, and the results show that the improved algorithm is more accurate to effectively find community structure compared with the original algorithm.
Keywords: Sync clustering algorithm, neighbors, similarity, neighborhood radius, community structure
