计算机与数字工程2018，Vol.46Issue(2)：213-217,240,6.DOI:10.3969/j.issn.1672-9722.2018.02.001
基于节点相似度的社团划分方法研究
Detecting Community Structure in Complex Networks Based on Node Similarity
摘要
Abstract
The detection of the community structure in networks is beneficial to understand the network structure and to ana-lyze the network properties.Most of conventional community detection methods focused on only considering the local information of the network to optimizing a certain objective function. However,these methods just have preference for specific types of networks but are not general.In present study,a new node similarity which captures global and local structures is proposed to detecting net-work structure.The presented method does not need any prior knowledge about the communities and its detection results are robust on the selection of the initial node.Some real-world and networks are used to evaluate the performance of the presented method.The simulation results demonstrate that this method is efficient to detect community structure in complex networks.关键词
复杂网络/节点相似度/社团划分Key words
complex networks/community detection/node similarity分类
信息技术与安全科学引用本文复制引用
甘立强,王旭阳,燕楠,王岚..基于节点相似度的社团划分方法研究[J].计算机与数字工程,2018,46(2):213-217,240,6.基金项目
国家自然科学基金项目(编号:11474300,61771461) （编号:11474300,61771461）
深圳市基础研究项目(编号:JCYJ20160429184226930)资助. （编号:JCYJ20160429184226930）
