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On a matrix-based measure of the degree of coreness of a node in a network

机译:基于矩阵的网络中节点核心程度的度量

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The paper focuses on the right and left eigenvectors of a network matrix that belong to the largest eigenvalue. It is shown that each of vector entries measures the walk centrality of the corresponding node’s position in the network’s link structure and of the positions of the node’s adjacent nodes; as a result, it indicates to which degree the node can be associated with the structure’s core, i.e., the structural coreness of the node. The relationship between the vectors’ coordinates and the position of the nodes, as well as the actual computation of the coordinates, is based on an iterative computational scheme known as the power method. The paper studies the method’s convergence for networks of different structure. Some possible applications are discussed. The paper also includes a numerical example dealing with a real network of 197 nodes and 780 links.
机译:本文着重研究了属于最大特征值的网络矩阵的左右特征向量。如图所示,每个向量条目都测量了相应节点在网络链接结构中的位置以及该节点相邻节点的位置的步行中心点;结果表明节点可以在多大程度上与结构的核心相关联,即节点的结构核心。向量的坐标与节点位置之间的关系以及坐标的实际计算是基于称为幂方法的迭代计算方案。本文研究了针对不同结构的网络的方法的收敛性。讨论了一些可能的应用。本文还包括一个处理197个节点和780个链接的真实网络的数值示例。

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