计算机科学 ›› 2022, Vol. 49 ›› Issue (11A): 210800177-5.doi: 10.11896/jsjkx.210800177

• 大数据&数据科学 • 上一篇    下一篇

基于k-shell熵的影响力节点的排序与识别

原慧琳1, 冯宠2   

  1. 1 东北大学秦皇岛分校管理学院 河北 秦皇岛 066004
    2 东北大学信息科学与工程学院 沈阳 110819
  • 出版日期:2022-11-10 发布日期:2022-11-21
  • 通讯作者: 冯宠(fengchong1997@163.com)
  • 作者简介:(1000289@neuq.edu.cn)
  • 基金资助:
    东北大学资助产学研战略合作项目(71971050);东北大学秦皇岛分校永辉超市股份有限公司产学研基地合作战略框架协议(7043902891801)

Ranking and Recognition of Influential Nodes Based on k-shell Entropy

YUAN Hui-lin1, FENG Chong2   

  1. 1 College of Management,Northeastern University,Qinhuangdao,Hebei 066004,China
    2 College of Information Science and Engineering,Northeastern University,Shenyang 110819,China
  • Online:2022-11-10 Published:2022-11-21
  • About author:YUAN Hui-lin,born in 1969,Ph.D,professor.Her main research interests include modeling and optimization of complex systems,information retrieval and artificial intelligence.
    FENG Chong,born in 1997,postgra-duate.His main research interests include complex network and artificial intelligence.
  • Supported by:
    Northeastern University Industry-University-Research Strategic Cooperation Project(71971050),Northeastern University Qinhuangdao Branch Yonghui-Supermarket Industry-University-Research Cooperation Strategic Framework Agreement(7043902891801).

摘要: 节点的影响力排序一直是复杂网络领域中最具有吸引力的一个问题,其对于衡量节点的传播能力有着重要的作用。由于网络中的节点的规模很大,研究者们希望能够更准确地估计节点的传播能力。文中基于信息论的基本概念和k-shell方法提出了一种新的影响力节点的排序方法,根据节点所在网络中的位置的拓扑信息来测量节点的传播能力。实验结果表明,该方法可以有效地识别网络中有影响力的节点,并且可以有效避免 k-shell法的“富人俱乐部现象”。

关键词: 复杂网络, 影响力节点, k-shell, 熵, 信息传播

Abstract: The spreading capacity of nodes has been one of the most attractive problems in the field of complex networks.Due to the large size of nodes in network,researchers want to find accurate measures to estimate the spreading capacity of nodes.In this paper,a new method is proposed based on the basic concepts of information theory and k-shell,which measures the spreading capacity of nodes according to the topological information of their locations in the network.Experimental results show that the proposed method is more effective than other similar methods,and can effectively avoid the “rich club phenomenon” of k-shell method.

Key words: Complex network, Influential node, k-shell entropy, Information spreading

中图分类号: 

  • TP311
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