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多尺度的社团结构稳定性分析
  • 摘要

    社团结构分析是一项非常重要且具有挑战性的工作,已经引起来自不同领域学者的广泛关注.在该文中,作者创新性地结合Potts模型和Markov动态过程,提出了衡量多尺度杜团结构稳定性的完整理论框架.对于给定的网络,该文通过揭示网络社团结构及其自旋动态的局域一致行为之间的关系,可以不使用特定的算法而直接获得社团结构相关的重要隐藏信息,比如社团结构的稳定性和在多个时间尺度的社团结构的最佳数量.它还克服了传统方法的不足,如模块度Q的分辨率局限性问题.进一步基于理论分析,该文给出一个无参数的社团结构探测算法.该算法通过计算每个节点的归属向量,可以识别网络的模糊社团结构,从而在多个层次上描述了每个节点参与重叠社团的程度.同时该文也证明了算法的可扩展性和在实际大型网络上的有效性.

  • 作者

    李慧嘉  李慧颖  李爱华  LI Hui-Jia  LI Hui-Ying  LI Ai-Hua 

  • 作者单位

    中央财经大学管理科学与工程学院 北京100081/清华大学自动化系 北京100084

  • 刊期

    2015年2期 ISTIC EI PKU

  • 关键词

    社团结构  Potts模型  Markov过程  稳定性  多尺度  社会计算  社交网络  复杂网络  community structure  Potts model  Markov process  stability  multi-scale  social computing  social networks  complex networks 

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