The research on detecting complex network community structure

Abstract

This paper mainly studies the complex network detection algorithm, and improves an algorithm based on K-means, Another reference node density properties, this paper puts forward a method community structure detection algorithms (BSTN) based on similarity between the nodes of the complex network, the algorithm greatly reduce iteration times, using the algorithm in the computer generated stochastic network known community structure, the result shows that this algorithm has higher accuracy than GN algorithm. Also in the actual network, this paper uses karate club network (karate network) and the American College Football club network (football network), experimental results compare to Newman algorithm, the proposed algorithm can have less iteration, approximate value of the module, it shows the BSTN algorithm is effective, and reasonable explain the community structure getting from the BSTN algorithm, the result of from the BSTN algorithm is practical, is reasonable.