Detecting Communities in Networks by Merging Cliques
Many algorithms have been proposed for detecting disjoint communities (relatively densely connected subgraphs) in networks. One popular technique is to optimize modularity, a measure of the quality of a partition in terms of the number of intracommunity and intercommunity edges. Greedy approximate algorithms for maximizing modularity can be very fast and effective. We propose a new algorithm that starts by detecting disjoint cliques and then merges these to optimize modularity. We show that this performs better than other similar algorithms in terms of both modularity and execution speed.
data mining network analysis community structure
Bowen Yan Steve Gregory
Department of Computer Science University of Bristol Bristol BS8 1UB,England
国际会议
上海
英文
832-836
2009-11-20（万方平台首次上网日期，不代表论文的发表时间）