%0 Journal Article
%T 基于影响簇选择模型和MCMC采样的社交圈子识别算法<br>An automatic detection algorithm for social circles based on influential cluster selection model and MCMC sampler
%A 黄佳鑫
%A 郭
%A 红
%A 郭
%A 昆
%J 福州大学学报(自然科学版)
%D 2015
%R 10.7631/issn.1000-2243.2015.05.0604
%X 提出一种新的紧密度公式和一种影响簇发现模型，并在此基础上设计基于局部社团探测的采样算法MCMCS_LCD，以及基于MCMCS_LCD的社交圈子自动识别算法SCD_MCMCS_LCD，算法综合考虑局部模块度和节点间紧密度. 在真实数据集上的实验表明，SCD_MCMCS_LCD算法在具有较快收敛速度的同时还具有较好的社交圈子识别效果.<br>This paper proposes a new expression of the close affinities and the influential cluster selection model，and on this basis to design an efficient sampler algorithm，called MCMCS_LCD，and further design an automatic detection method called SCD_MCMCS_LCD. The algorithm takes account into both local modularity M and close affinities. Experiments demonstrate that SCD_MCMCS_LCD has a faster convergence speed while still maintains a good social circle recognition effect
%K 社交网络 社交圈子识别 马尔科夫蒙特卡洛采样 局部社团探测&lt
%K br&gt
%K social network social circles discovering MCMC sampler local community detection
%U http://xbzrb.fzu.edu.cn/ch/reader/view_abstract.aspx?file_no=201505006&flag=1