基于二项熵和邻域节点间范德华力的关键节点识别方法

对节点重要性进行排序是复杂网络中识别关键节点的一种常用分析方法,分析网络中节点的重要性,有助于深入了解网络特性。在现有方法上为进一步提升节点评估精准度,引入二项熵概念来量化节点在网络中的重要性,通过邻域相似度衡量节点间的相互影响力,同时采用范德华力抽象节点之间的相互作用关系,提出一种基于二项熵和邻域节点间范德华力的关键节点识别方法,该方法从网络的整体信息流和相邻节点之间的位置和交互关系,综合考虑节点的局部和全局特征,并选取3个同类算法通过3个评价指标验证性能优劣,实验结果表明该算法对重要节点的判断具有良好的性能。

Identification Method Based on Binomial Entropy and Van der Waals Forces between Neighboring Nodes

Ranking importance in nodes is a commonly used analysis method for identifying key nodes in complex networks, and importance of analyzing nodes in the network is a great help to a deeper understanding network characteristics. In order to further improve the accuracy of node evaluation based on existing methods, this paper introduces the concept of Binomial Entropy to quantify the importance of nodes in the network, measures the mutual influence between nodes through neighborhood similarity, and simultaneously uses Van der Waals force to abstract the interaction between nodes. Therefore, a key node identification method based on binomial entropy and Van der Waals force between neighboring nodes is proposed. This method is a comprehensive consideration of the local and global characteristics of nodes from the overall information flow of the network and the location and interaction relationship between adjacent nodes, and a selection from three similar algorithms to verify the performance through three evaluation indicators. The experimental results show that the algorithm in this paper is good in performance in judging important nodes.