摘要
网络拓扑结构及节点间的相对距离对复杂网络节点的重要程度具有较大影响。在分析并研究现有节点重要性评估方法的基础上,根据邻居节点的拓扑结构并结合万有引力定律,提出一种基于改进重力中心性的复杂网络节点重要性评估方法。实验从SIR传播模型的准确性和单调性两方面验证了该方法的有效性,且结果表明其可对节点重要性进行重新排序,相比度中心性、介数中心性等方法能更准确地评估复杂网络节点的传播能力与重要性。
The topological structure of network and the relative distance between nodes have a significant influence on the importance of complex network nodes.Based on the analysis and study of the existing evaluation methods for node importance,this paper combines the topological structure of neighbor nodes with the law of universal gravitation,and proposes a new evaluation method for node importance in complex network based on Improved Gravity Centrality(IGC). Experimental results demonstrate the effectiveness of the proposed method in terms of the accuracy and monotony of the SIR transmission model,and results show that the model can resort the node importance,outperforming Degree Centrality(DC),Betweenness Centrality(BC) and other methods in evaluating the transmission ability and importance of complex network nodes.
作者
张宪立
唐建新
ZHANG Xianli;TANG Jianxin(School of Computer and Communication,Lanzhou University of Technology,Lanzhou 730050,China)
出处
《计算机工程》
CAS
CSCD
北大核心
2021年第2期139-145,151,共8页
Computer Engineering
基金
浙江省自然科学基金(LQ20F020011)。
关键词
社交网络
拓扑结构
节点重要性
万有引力定律
重力中心性
social network
topological structure
node importance
law of universal gravitation
gravity centrality
