基于标签传播识别网络中的关键节点
发布时间：2018-10-30 16:21
【摘要】：基于标签传播动力学提出了一种识别网络关键节点的算法,主要思想是把每个节点接收到不同标签的数量作为判断节点重要性的指标。应用两种不同的传播模型,在不同网络上与其它中心性指标作比较。结果表明:基于标签传播的中心性指标比其它的中心性方法可以更好地识别网络中的关键节点。基于标签传播的中心性指标还具有以下优势:不需要利用网络的结构信息,因此可以推广到大规模网络上;揭示了一种现象——好的接收者往往也是好的传播者。
[Abstract]:Based on label propagation dynamics, an algorithm is proposed to identify the key nodes in the network. The main idea is to take the number of different tags received by each node as the index to judge the importance of the nodes. Two different propagation models are used to compare with other central indexes in different networks. The results show that the centrality index based on label propagation can better identify the key nodes in the network than other centrality methods. The central index based on label propagation also has the following advantages: it does not need to use the structural information of the network, so it can be extended to large-scale networks; it reveals a phenomenon that good receivers are often good communicators.
【作者单位】： 安徽大学数学科学学院;
【基金】：国家自然科学基金(61473001) 博士启动资金(01001951)
【分类号】：O157.5
[Abstract]:Based on label propagation dynamics, an algorithm is proposed to identify the key nodes in the network. The main idea is to take the number of different tags received by each node as the index to judge the importance of the nodes. Two different propagation models are used to compare with other central indexes in different networks. The results show that the centrality index based on label propagation can better identify the key nodes in the network than other centrality methods. The central index based on label propagation also has the following advantages: it does not need to use the structural information of the network, so it can be extended to large-scale networks; it reveals a phenomenon that good receivers are often good communicators.
【作者单位】： 安徽大学数学科学学院;
【基金】：国家自然科学基金(61473001) 博士启动资金(01001951)
【分类号】：O157.5
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