Clustering Graph Based on Edge Linking Coefficient
In this paper, we introduce the concept of Edge Linking Coefficient(ELC), which is a value positively proportional to the number of the common neighbors shared by a pair of connected nodes and used as the measurement of the connection strength between them, and present a new divisive clustering algorithm for discovering communities hidden in large-scale complex networks based on it Combining with the weak and the strong criteria of the communities, the ELCA method can effectively identify community structure in networks, which is shown in the experimental results on the synthetic and four real-world network data sets. In addition, the clustering algorithm is much faster than the GN algorithm and its variants, and suitable to the large-scale complex network clustering.
complex network graph clustering community edge linking coefficient
Zongwei Jia Jun Cui Wei Li
School of Information Science and Engineering Shanxi Agricultural University Taigu, China School of Computer & Information Technology Shanxi University Taiyuan, China
国际会议
太原
英文
42-46
2010-10-22（万方平台首次上网日期，不代表论文的发表时间）