计算机工程与科学2017，Vol.39Issue(7)：1273-1280,8.DOI:10.3969/j.issn.1007-130X.2017.07.011
基于节点依赖度和相似社团融合的社团结构发现算法
A community detection algorithm based on node dependence and similar community fusion
摘要
Abstract
As one of the topological properties of complex networks,the community structure has important theoretical and practical significance.We propose a community detection algorithm based on node dependence and the fusion of similar communities.The algorithm firstly divides the whole network into several local networks with large average clustering coefficients,thus constructing a skeleton of the complex networks.Then according to the definition of connectivity,the algorithm continuously absorbs the edge nodes of the community and small communities into the backbone network until all the nodes are accurately allocated to the community.This algorithm is applied to Zachary Karate Club network and the dolphin social network,and compared with the Girvan-Newman algorithm (GN) and Newman fast algorithm (NFA).The results show that our algorithm can effectively classify fuzzy edge nodes and the result of the community division has high accuracy.关键词
复杂网络/社团发现/依赖度/相似社团Key words
complex networks/community detection/dependence degree/similar community分类
信息技术与安全科学引用本文复制引用
聂祥林,张玉梅,吴晓军,吴霞..基于节点依赖度和相似社团融合的社团结构发现算法[J].计算机工程与科学,2017,39(7):1273-1280,8.基金项目
国家自然科学基金(11172342,11372167,11502133) （11172342,11372167,11502133）
陕西省重点科技创新团队项目(2014KTC-18) （2014KTC-18）
西安市科技计划项目(CXY1437(1)) （CXY1437(1）
榆林市科技计划(2014cxy-09,sf13-43,2012 cxy3-6) （2014cxy-09,sf13-43,2012 cxy3-6）
