南京理工大学学报（自然科学版）2016，Vol.40Issue(3)：267-271,5.DOI:10.14177/j.cnki.32-1397n.2016.40.03.003
基于复杂网络的社区发现算法
Community detection algorithm based on complex network
杨晓光 1朱保平1
作者信息
- 1. 南京理工大学计算机科学与工程学院，江苏南京210094
- 折叠
摘要
Abstract
To solve the problem of low accuracy of existing community detection methods , a community detection algorithm based on central nodes is proposed here .Central nodes of communities are found through the degree of each node and the similarity of nodes .Each community is optimized using local modules .The community division of the entire network is obtained by classifying isolated nodes and overlapping community nodes to their community as far as possible based on node attraction .The algorithm proposed here is compared with three local community detection algorithms and four global community detection algorithms respectively .Experimental results show that the algorithm can improve the accuracy of the community detection and is feasible .关键词
复杂网络/社区发现/中心节点/局部模块度/节点吸引力/孤立节点/重叠社区节点Key words
complex network/community detection/central nodes/local modules/node attraction/isolated nodes/overlapping community nodes分类
信息技术与安全科学引用本文复制引用
杨晓光,朱保平..基于复杂网络的社区发现算法[J].南京理工大学学报（自然科学版）,2016,40(3):267-271,5.
