The Research on Detecting Complex Network Community Structure
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 BSTIN 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.
Complex networks Community structure K-means Newman algorithm Module degrees
Wang Zongjiang
Computer and Communication Engineering WeiFang University WeiFang,China
国际会议
上海
英文
163-166
2011-03-11（万方平台首次上网日期，不代表论文的发表时间）