A Density-based Seed-Centric Community Detection Algorithm
Although many different community detection algorithms have been proposed to detect community structures in complex networks, how to effectively detect community structures is still a great challenge.Seed-centric methods is one of the most effective solutions for community detection.To more, in this paper, we propose a novel density-based seed expansion algorithm, namely, DenSeC, which can easily find cores of communities.By taking nodes with higher density locally as cores of communities, DenSeC first detects cores by searching from sparsely connected area to densely connected area.Then, starting from cores, along the path from densely connected area to sparsely connected area, it constructs a community by iteratively adding nodes which are similar to the nodes in the community.Numerical experiments have verified the effectiveness of DenSeC.
Community Detection Density Seed Expansion
Wei Liu Mei Chen Kun Liu Yang Zhou Xiaoyun Chen
School of Information Science and Engineering Lanzhou University Lanzhou, China School of Information Science and Engineering Lanzhou University Lanzhou, China;School of Electronic
国际会议
武汉
英文
149-154
2016-09-23（万方平台首次上网日期，不代表论文的发表时间）