自动化学报2013，Vol.39Issue(7)：1117-1125,9.DOI:10.3724/SP.J.1004.2013.01117
基于核心图增量聚类的复杂网络划分算法
Complex Network Community Detection Based on Core Graph Incremental Clustering
摘要
Abstract
This paper references the principle of clustering in clustering-based method for the unsupervised intrusion detection algorithm (CBUID),and proposes a clustering-based method for community detection (CBCD).We propose a method of community summary building,and give the formula of the similarity between node and community.First,it detects communities on the core network composed of a small amount of high-degree core nodes,then partitions the remaining nodes into core community according to the similarity between the node and community incrementally.Its running time mainly depends on the network size,the number of edges and the number of communities,and our algorithm has essentially a linear time complexity.Applications on several common real networks demonstrate that this method is very effective at community detection of networks.关键词
复杂网络/社区摘要/相似度/社区发现Key words
Complex networks/community summary/similarity/community detection引用本文复制引用
张新猛,蒋盛益..基于核心图增量聚类的复杂网络划分算法[J].自动化学报,2013,39(7):1117-1125,9.基金项目
国家自然科学基金(61070061),教育部人文社会科学研究青年基金项目(11YJCZH086,12YJCZH281,13YJCZH258)资助 （61070061）
Supported by National Natural Science Foundation of China (61070061),the Youth Project of Humanity and Social Science for Ministry of Education (llYJCZH086,12YJCZH281,13YJCZH258) （61070061）
