基于网络超链接信息熵的节点重要性序结构演化建模分析

The Model to Analyses of Node Importance Order Structure Evolution Based on Network Hyperlink Information Entropy

动态复杂网络在时空演化过程中,网络节点重要性层内交互关系和层间耦合关系可以更为准确对时序网络节点序结构演化进行分析.本文提出基于网络超链接信息熵的节点重要性序结构演化模型.分析时序网络层内节点超链接信息熵重要性排序结果,得到时序网络节点相邻时间层与跨时间层节点重要性排序模型.节点超链接信息熵总结相邻时间层与跨时间层节点相似性耦合效应.通过SIR(Susceptible Infected Recovered)模型检验节点传播效率进行实证网络仿真,结果与经典时序网络模型相比,本文模型Kendall’sτ值在各时间层均有提高,最高为11.310%.

In the time evolution of dynamic complex networks,the intra-layer interaction relationship and inter-layer coupling relationship of the importance of network nodes can be more accurately analyzed for the evolution of the node order structure of the time ordered networks.In this paper,a model of node importance order structure evolution based on network hyperlink information entropy is proposed.Through the results of the importance ranking of node hyperlink information entropy within the temporal network layer,the importance ranking model of nodes in the adjacent temporal layer and across temporal layers of the temporal network is analyzed.The entropy of node hyperlink information summarizes the coupling effect of similarity between adjacent temporal layers and inter-temporal layers.An empirical network simulation was conducted to check the node propagation efficiency by SIR(Susceptible Infected Recovered)model.Compared with the classical temporal network model,the Kendall’sτvalue of this model was improved in all time layers,with the highest value of11.310%.