detectingcommunitystructurefromparsimonytoweightedparsimony

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	detectingcommunitystructurefromparsimonytoweightedparsimony
	Zhang Xiangsun; Zhang Junhua; Qiu Yuqing
	2010
发表期刊	journalofsystemsscienceandcomplexity
ISSN	1009-6124
卷号	000 期号:005 页码:1024
摘要	Community detection has attracted a great deal of attention in recent years. A parsimony criterion for detecting this structure means that as minimal as possible number of inserted and deleted edges is needed when we make the network considered become a disjoint union of cliques. However, many small groups of nodes are obtained by directly using this criterion to some networks especially for sparse ones. In this paper we propose a weighted parsimony model in which a weight coefficient is introduced to balance the inserted and deleted edges to ensure the obtained subgraphs to be reasonable communities. Some benchmark testing examples are used to validate the effectiveness of the proposed method. It is interesting that the weight here can be determined only by the topological features of the network. Meanwhile we make some comparison of our model with maximizing modularity Q and modularity density D on some of the benchmark networks, although sometimes too many or a little less numbers of communities are obtained with Q or D, a proper number of communities are detected with the weighted model. All the computational results confirm its capability for community detection for the small or middle size networks.
语种	英语
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/38872
专题	应用数学研究所
作者单位	中国科学院数学与系统科学研究院
推荐引用方式 GB/T 7714	Zhang Xiangsun,Zhang Junhua,Qiu Yuqing. detectingcommunitystructurefromparsimonytoweightedparsimony[J]. journalofsystemsscienceandcomplexity,2010,000(005):1024.
APA	Zhang Xiangsun,Zhang Junhua,&Qiu Yuqing.(2010).detectingcommunitystructurefromparsimonytoweightedparsimony.journalofsystemsscienceandcomplexity,000(005),1024.
MLA	Zhang Xiangsun,et al."detectingcommunitystructurefromparsimonytoweightedparsimony".journalofsystemsscienceandcomplexity 000.005(2010):1024.