Abstract

Key nodes identification is an important way to analyze and understand the characteristics, structure, and functions of the complex network. In this paper, links in complex networks are taken as the basic unit, and the overlapping community in complex networks is obtained through the clustering analysis of links. Then, the importance of the node is judged according to the number of associations containing the node and the weight value of the association in the network, because the nodes Shared between communities have more influence on the functional structure of the network. Finally, the method is applied to rank the importance of nodes in IEEE standard 300 node system, and the results are verified by network conductivity. The comparison with the results of the Betweenness algorithm, HITS algorithm and Pagepank algorithm shows that the method presented in this paper can effectively identify the key nodes from the complex network.

中文翻译：

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基于重叠社区结构的定向网络关键节点识别

摘要

关键节点识别是分析和了解复杂网络的特征，结构和功能的重要方式。本文以复杂网络中的链接为基本单元，通过对链接的聚类分析获得复杂网络中的重叠社区。然后，由于社区之间共享的节点对网络的功能结构影响更大，因此根据包含该节点的关联数和该关联在网络中的权重值来判断该节点的重要性。最后，将该方法应用于IEEE标准300节点系统中节点的重要性排序，并通过网络传导性验证了结果。与Betweenness算法的结果进行比较，