基于密度峰值聚类法的节点重要性研究

Research on Node Importance Based on Density Peak Clustering Method

复杂网络中,识别有影响力的节点一直是一个重要的研究课题,备受学者的关注。本文提出了一种基于密度峰值聚类的中心性指标(Gam)来对整个网络中的节点进行排序。通过在实际网络上的实验结果表明,与已知的DC、BC、CC等中心性指标相比,Gam指标在不同的真实网络中表现优异。

In complex networks, identifying influential nodes has always been an important research topic and has attracted the attention of scholars. In this paper, we propose a centrality based on density peak clustering （Gain） to rank the nodes in the complex network. The experimental results on the real network show that, compared with the traditional methods DC, BC, CC, ere, the Gain centrality performs well in different real networks.