无标度网络的分类特性

V. Shergin, L. Chala, S. Udovenko
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引用次数: 2

摘要

节点的度分布是复杂网络最重要的特征,但不是全面的特征。度分布是一阶图度量,分类度是二阶图度量。选型系数是衡量网络中节点以某种方式与相似或不同节点连接的趋势。作为最简单的情况,分类混合是根据节点度来考虑的。总体而言,度分布对网络结构和分类系数边界都构成了本质的制约。研究了具有极端选型系数的SF-网络结构的确定问题。找到了分类系数的边界估计。研究发现,当sf模型的标度因子与ba模型的标度因子相差甚远时,这些边界就会变宽。此外,边界随着网络规模的增大而缩小。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assortativity Properties of Scale-Free Networks
Nodes distribution by degrees is the most important characteristic of complex networks, but not comprehensive one. While degree distribution is a first order graph metric, the assortativity is a second order one. Assortativity coefficient is a measure of a tendency for nodes in networks to connect with similar or dissimilar ones in some way. As a simplest case, assortative mixing is considered according to nodes degree. In general, degree distribution forms an essential restriction both on the network structure and on assortativity coefficient boundaries. The problem of determining the structure of SF- networks having an extreme assortativity coefficient is considered. The estimates of boundaries for assortativity coefficient have been found. It was found, that these boundaries are as wider as scaling factor of SF-model is far from one of BA-model. In addition, the boundaries are narrowing with increasing the network size.
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