基于加权方法的节点重要性度量

Measuring node importance based on weighted nonlinear method

网络中节点重要性度量对于信息的扩散、产品的曝光、传染性疾病的检测等都具有重大的理论意义。为了度量节点重要性,基于网络拓扑结构考虑全局信息和局部信息提出了加权的节点重要性度量方法。对于一个无权网络,先考虑网络全局信息,计算出每个节点的特征中心向量值,将边两端节点值的和作为边的权重,从而构成一个加权网络;然后根据加权网络的局部信息求出加权网络的度。基于SIR模型的四个实证网络,实验结果表明加权方法比特征向量中心性、度中心性、紧密度中心性和介数中心性方法的效果更显著。

Identifying the node importance in the network is of significance for information diffusion,product exposure,contagious disease detection,and so on.In order to measure the node importance based on the network topology,this paper presented a weighted method by taking into account the global and local information.Specifically,for an unweighted network,the link weight was the sum of the eigenvector of a pair of nodes connected by this link.Based on the local information,it calculated the node’s importance by the node’s link weight.According to the SIR simulation on four real networks,the weighted method can rank the node influence more accurately than eigenvector centrality,degree,closeness centrality and betweenness centrality.