A new evidential methodology of identifying influential nodes in complex networks
A new evidential methodology of identifying influential nodes in complex networks
复制标题
识别复杂网络中有影响力节点的新证据方法
DOI：
10.1016/j.chaos.2017.05.040
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发表时间：
2017-10-01
影响因子：
7.8
通讯作者：
Deng, Yong
中科院分区：
文献类型：
--
作者：
Bian, Tian;Deng, Yong
在复杂网络领域，如何识别复杂网络中有影响力的节点仍然是一个开放的研究课题。在现有的证据中心性(EVC)中，没有考虑复杂网络中的全局结构信息。此外，EVC还具有只能应用于加权网络的局限性。通过对EVC生成的基本概率分配(BPA)强度进行修正，提出了一种新的证据中心性(NEC)。根据网络中节点之间的最短路径，而不是只考虑局部信息，构造了一些其他的BPA。利用修正的Dempster-Shafer证据理论组合规则，确定了新的中心性度量。数值算例表明了该方法的有效性。(C)2017爱思唯尔有限公司。保留所有权利。
In the field of complex networks, how to identify influential nodes in complex networks is still an open research topic. In the existing evidential centrality (EVC), the global structure information in complex networks is not taken into consideration. In addition, EVC also has the limitation that only can be applied on weighted networks. In this paper, a New Evidential Centrality (NEC) is proposed by modifying the Basic Probability Assignment (BPA) strength generated by EVC. According to the shortest paths between the nodes in the network rather than just considering local information, some other BPAs are constructed. With a modified combination rule of Dempster-Shafer evidence theory, the new centrality measure is determined. Numerical examples are used to illustrate the efficiency of the proposed method. (C) 2017 Elsevier Ltd. All rights reserved.