摘要
通过提取出具有高链接密度的局部团,从局部团出发进行扩展社区,设计自动选择社区扩展的终止条件,以保留最优社区结构,提出一种社会网络局部社区识别算法。在人工生成网络和真实网络上的实验结果表明,与同类算法相比,该算法能够识别出稳定的局部社区结构,提升了局部社区识别结果的准确率。
The local clique with high link density is extracted,the community is extended from the local clique,the termination conditions for automatic selecting community expansion are designed to retain the optimal community structure,and an algorithm for identifying local community of social network is proposed. The experimental results for the artificial network and real network show that compared with the existing algorithm,the given algorithm can identify the stabile local community structure and enhance the accuracy of the local community identification results.
出处
《信息技术》
2016年第3期19-23,27,共6页
Information Technology
基金
广西自然科学基金(2014GXNSFAA118396)
广西研究生教育创新计划项目(YCSZ2014034)
关键词
社会网络
局部社区识别
局部团
局部链接密度
social network
local community identification
local clique
local link density