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复杂网络中连通支配中心性的计算

  • 徐敏政 ,
  • 许珺 ,
  • 陈娱
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  • 1.中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室,北京 100101;
    2.中国科学院大学资源与环境学院,北京 100049
徐敏政(1990-),男,江西抚州人,硕士研究生,主要研究方向为地理信息检索、空间数据挖掘。

收稿日期: 2013-08-09

  网络出版日期: 2026-06-22

基金资助

国家高技术研究发展计划(863)基金(2012AA12A211);国家自然科学基金(41371380)

The Calculation of Connected Dominating Centrality in Complex Network

  • XU Minzheng ,
  • XU Jun ,
  • CHEN Yu
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  • 1. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;
    2. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China

Received date: 2013-08-09

  Online published: 2026-06-22

摘要

分析了现实生活中对重要节点的需求背景,对连通的网络模型提出了一种新型中心性评价指标,连通支配中心性。该中心性利用网络连通支配集的“连通”和“支配”两大特性,通过循环构建点导出支配子图的连通支配集,生成一棵支配关系扩展有向树。然后基于各节点在该有向树中的支配层次数,支配数和支配边权值3方面的属性,设计了反映节点支配能力强弱的中心性计算公式。最后以合作关系图为例进行相应实验,发现连通支配中心性比较高的节点不仅构成了网络的骨干网,能较好地维持网络基本形态,而且能桥接几个不同研究分区,起到一定的中介作用,体现了网络中节点的组织控制能力。

本文引用格式

徐敏政 , 许珺 , 陈娱 . 复杂网络中连通支配中心性的计算[J]. 复杂系统与复杂性科学, 2014 , 11(4) : 41 -47 . DOI: 10.13306/j.1672-3813.2014.04.008

Abstract

In this paper, we propose a novel centrality called connected dominating centrality according to the real-life demand analysis. The connected dominating set of a network has two characteristics, connectivity and dominance. Based on the two characteristics, we recursively construct the connected dominating sets of the induced dominating sub graphs and generate a directed spanning tree with dominating relationships. By combining the number of nodes dominated by a node, its hierarchical level in the directed spanning tree, and the weights of the edges which connect the dominator and its dominated nodes, we define the calculation formula of our proposed connected dominating centrality. To verify the effectiveness of the centrality, an experiment is made on the paper co-author network of an international journal. The experimental results show that the nodes with higher connected dominating centrality constitute the backbone network and can maintain the shape of network well. Some of them bridge different research communities; others are the kernels of communities. They have good ability in organizing and controlling the network.

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