基于WB-MMSB模型的微博网络社区发现
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  • 英文篇名:Community Detection for Micro-blog Network Based on WB-MMSB Model
  • 作者:徐建民 ; 武晓波 ; 吴树芳 ; 粟武林
  • 英文作者:XU Jian-min;WU Xiao-bo;WU Shu-fang;SU Wu-lin;College of Mathematics and Computer,Hebei University;College of Management,Hebei University;
  • 关键词:微博网络 ; 社区发现 ; 混合隶属度随机块模型 ; 重叠社区
  • 英文关键词:Micro-blog network,Community detection,Mixed membership stochastic block model,Overlapping commu-nities
  • 中文刊名:JSJA
  • 英文刊名:Computer Science
  • 机构:河北大学数学与计算机学院;河北大学管理学院;
  • 出版日期:2015-03-15
  • 出版单位:计算机科学
  • 年:2015
  • 期:v.42
  • 基金:中国博士后科学基金项目(20070420700);; 河北省自然科学基金项目(F2011201146)资助
  • 语种:中文;
  • 页:JSJA201503014
  • 页数:6
  • CN:03
  • ISSN:50-1075/TP
  • 分类号:70-75
摘要
提出了一个用于微博网络社区发现的模型WB-MMSB,该模型考虑了微博网络中节点存在的单向关系,节点的社区隶属度从链入主题隶属度和链出主题隶属度两个方面表示。用指数族分布和平均场变分推理方法推导了模型中各变量的表示,并用SVI算法计算模型涉及的参数。实验在新浪微博数据集上进行,采用归一化互信息和困惑度进行评估,结果表明,WB-MMSB模型的社区发现能力优于aMMSB模型,并且其收敛速度快于aMMSB模型。
        Considering the nodes of Mico-blog network have single direction relations,a new model WB-MMSB was put forward for community detection,which uses directed edges to embody the direction relations of nodes,and two aspects link-in and link-out are used to quantify the community membership of nodes.Exponential family distribution and meanfield variational inference method were used to inference the representations of variables in this model,and SVI algorithm was used to compute relating parameters.Experiments adopted Sina-Weibo dataset and NMI to testify the performance of WB-MMSB.The results indicate that the community detection ability of WB-MMSB model is better than aMMSB model,and the convergence rate of WB-MMSB model is faster than aMMSB model.
引文
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