中心性
计算机科学
节点(物理)
度量(数据仓库)
复杂网络
基础(线性代数)
财产(哲学)
数据挖掘
网络科学
拓扑(电路)
数学
结构工程
认识论
组合数学
工程类
万维网
哲学
几何学
标识
DOI:10.1016/j.knosys.2021.107198
摘要
To find the important nodes in complex networks is a fundamental issue. A number of methods have been recently proposed to address this problem but most previous studies have the limitations, and few of them considering both local and global information of the network. The location of node, which is a significant property of a node in the network, is seldom considered in identifying the importance of nodes before. To address this issue, we propose an improved gravity centrality measure on the basis of the k-shell algorithm named KSGC to identify influential nodes in the complex networks. Our method takes the location of nodes into consideration, which is more reasonable compared to original gravity centrality measure. Several experiments on real-world networks are conducted to show that our method can effectively evaluate the importance of nodes in complex networks.
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