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具有可调聚类的无标度网络增长

Growing scale-free networks with tunable clustering.

作者信息

Holme Petter, Kim Beom Jun

机构信息

Department of Theoretical Physics, Umeå University, 901 87 Umeå, Sweden.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2002 Feb;65(2 Pt 2):026107. doi: 10.1103/PhysRevE.65.026107. Epub 2002 Jan 11.

DOI:10.1103/PhysRevE.65.026107
PMID:11863587
Abstract

We extend the standard scale-free network model to include a "triad formation step." We analyze the geometric properties of networks generated by this algorithm both analytically and by numerical calculations, and find that our model possesses the same characteristics as the standard scale-free networks such as the power-law degree distribution and the small average geodesic length, but with the high clustering at the same time. In our model, the clustering coefficient is also shown to be tunable simply by changing a control parameter---the average number of triad formation trials per time step.

摘要

我们扩展了标准的无标度网络模型,使其包含一个“三元组形成步骤”。我们通过解析和数值计算两种方式分析了该算法生成的网络的几何特性,发现我们的模型具有与标准无标度网络相同的特征,如幂律度分布和较短的平均测地线长度,但同时具有较高的聚类系数。在我们的模型中,聚类系数也被证明可以通过改变一个控制参数——即每个时间步的三元组形成试验的平均次数——来进行调节。

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