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复杂网络中的层次度量

Hierarchy measures in complex networks.

作者信息

Trusina Ala, Maslov Sergei, Minnhagen Petter, Sneppen Kim

机构信息

Department of Physics, Umeå University, 90187 Umeå, Sweden.

出版信息

Phys Rev Lett. 2004 Apr 30;92(17):178702. doi: 10.1103/PhysRevLett.92.178702. Epub 2004 Apr 29.

Abstract

Using each node's degree as a proxy for its importance, the topological hierarchy of a complex network is introduced and quantified. We propose a simple dynamical process used to construct networks which are either maximally or minimally hierarchical. Comparison with these extremal cases as well as with random scale-free networks allows us to better understand hierarchical versus modular features in several real-life complex networks. For random scale-free topologies the extent of topological hierarchy is shown to smoothly decline with gamma, the exponent of a degree distribution, reaching its highest possible value for gamma</=2 and quickly approaching zero for gamma>3.

摘要

以每个节点的度作为其重要性的代理,引入并量化了复杂网络的拓扑层次结构。我们提出了一个简单的动力学过程来构建最大或最小层次结构的网络。与这些极端情况以及随机无标度网络进行比较,使我们能够更好地理解几个现实生活中的复杂网络中的层次结构与模块化特征。对于随机无标度拓扑,拓扑层次的程度显示随着γ(度分布的指数)而平滑下降,对于γ≤2达到其最高可能值,对于γ>3则迅速接近零。

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