科研之友
微信
新浪微博
Facebook
分享链接
摘要
Community detection plays an important role in the complex networks. Modularity is the most widely used measure of the partition quality. In this paper, we present a community detection method for optimizing the modularity. We use the idea of multilevel paradigm to improve the state-of-the-art detection algorithm BGLL. Our method contains three phases: cluster phase, modularity optimization phase, and refinement phase. Experimental results on a set of well-known benchmark networks show that, our method is efficient and can obtain equal or greater max modularity for all tested benchmark networks.
- 出版日期2014
- 单位福州大学
