基于熵的节点重要度评估方法

Entropy based node importance evaluation method

针对网络中关键节点识别问题,提出一种基于熵的有向加权网络节点重要度评估方法,即EnRank算法。通过定义有向加权网络中各个节点吸引率AR和传输率TR,运用熵法对节点的度、吸引率和传输率进行综合运算,从而得出有关于节点重要性综合评价指标。该算法既考虑了节点本身的重要性,也考虑了相邻节点对其相对重要性。经过对ARPA网络及社交网络连锁故障仿真实验,验证了该方法的可靠性。

Aiming at the problem of identifying key nodes in a network,an entropy based network node importance evaluation method,namely EnRank algorithm,is proposed.By defining the attraction rate AR and the transmission rate TR of each node in the directed weighted network,the degree,attraction rate and transmission rate of the node are comprehensively calculated by entropy method,and the comprehensive evaluation index of node importance is obtained.The algorithm considers both the importance of nodes themselves and the relative importance of neighboring nodes.The reliability of the method is verified by simulation experiments on ARPA network and social network.