引文网络的无标度模型

Ming-Yang Wang, Guang Yu, Daren Yu
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引用次数: 5

摘要

优先附着机制(PAM)被认为是构成复杂网络无标度拓扑结构的核心成分之一。在之前的工作中,我们研究了一个典型的现实世界的复杂网络-引文网络,通过考虑节点在度中的动态引文属性来研究PAM。提出短期优先依恋机制(SMPAM),探讨引文网络无标度拓扑结构形成的原因。在SMPAM的基础上,我们进一步提出了引文网络的无标度网络模型。该模型仅考虑论文在最近一年内获得的引用数来确定附着率。采用平均场法推导了引文网络的度分布,发现模型演化为幂律指数r=2的无标度网络。仿真结果表明,引文网络具有良好的幂律分布,验证了模型的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The scale-free model for citation network
Preferential attachment mechanism (PAM) is considered to be one of the kernel ingredients in forming the scale-free topology of complex networks. In our previous work, we investigated the PAM for a typical real-world complex network—citation network by considering the dynamic citation properties in nodes' in-degree. And the short-term preferential attachment mechanism (SMPAM) is proposed to explore the reason for forming the scale-free topology of citation network. Basing on SMPAM, we further proposed a scale-free network model for citation network. The model just considers the citations that papers obtained in the recent one-year period to determine the attachment rate. Taking the mean field method, we deduced the degree distribution of citation network and found that the model evolving into a scale-free network with the power-law exponent r=2. The results by simulation also show a good power-law distribution of citation network, which exhibits the validity of the model proposed.
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