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基于优化理论的社区无标度网络模型
  • 摘要

    当前建模社区无标度网络的研究多基于组合法,即先构造无标度特征再构造社区特征,或者先构造社区特征再构造无标度特征.基于组合法的模型能生成令人满意的社区无标度网络,但是该方法需要满足社区大小相等、社区特征和无标度特征间的顺序依赖等特定条件,而这些特定条件在真实网络的演化中往往并不存在.值得注意的是,多数学者同意社区网络起源于网络节点之间的类别距离,如地理距离、兴趣距离、偏好距离等,但现有研究尚未确证社区结构与类别距离之间的因果关系.针对组合法的缺点和社区特征起源的问题,该文建立了一个优化模型,该模型以无标度属性为优化目标,以类别距离为约束条件.仿真结果表明该模型揭示了类别距离与社区特征间的因果关系,能生成多种参数下的社区无标度网络,更好地拟合了现实世界中的社区无标度网络.

  • 作者

    吴泓润  覃俊  易云飞  李德毅  郑波尽  WU Hong-Run  QIN Jun  YI Yun-Fei  LI De-Yi  ZHENG Bo-Jin 

  • 作者单位

    武汉大学软件工程国家重点实验室 武汉430072/中南民族大学计算机学院 武汉430074/武汉大学软件工程国家重点实验室 武汉430072;河池学院计算机与信息工程学院 广西宜州 546300/清华大学软件学院 北京 100084

  • 刊期

    2015年2期 ISTIC EI PKU

  • 关键词

    社区结构网络  无标度网络  优化理论  类别距离  社交网络  社会计算  复杂网络  community-structure networks  scale-free networks  optimization theory  similarity distance  social networks  social computing  complex networks 

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