南京理工大学学报（自然科学版）2017，Vol.41Issue(1)：35-40,6.DOI:10.14177/j.cnki.32-1397n.2017.41.01.005
基于三角模体的社团发现算法
Community discovery algorithm based on triangular motifs
孙圣波 1朱保平 1杨晓光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
In order to improve the efficiency of community detection algorithm,this paper proposes a community structure discovery based on the triangular motifs and expectation-maximization models of a community discovery algorithm.The model based on the triangle motif represents the network,considering the links between nodes and mixed membership between communities.The expectation maximization algorithm is used to solve the parameters of the model,triangle motif and bilateral triangular norm body as an object of calculation by reducing the calculation object to improve the efficiency of the algorithm.The results are obtained according to the parameters of node membership links and associations between communities.The experimental results show that the algorithm can improve the efficiency of the community discovery and ensure the capacity of the community discovery.关键词
三角模体/社团发现/期望极大算法/混合隶属度/链接关系Key words
triangular motifs/community discovery/expectation-maximization algorithm/mixed membership degree/link relationship分类
信息技术与安全科学引用本文复制引用
孙圣波,朱保平,杨晓光..基于三角模体的社团发现算法[J].南京理工大学学报（自然科学版）,2017,41(1):35-40,6.
