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arXiv physics/0607134physics.soc-ph
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加权分配与分配网络模型

Weighted Assortative And Disassortative Networks Model

C. C. Leung, H. F. Chau

摘要:

现实世界的网络处理结构化连接,因为它们具有非平凡的顶点度相关性和聚类性。在这里,我们提出了一个玩具模型的结构形成在现实世界中的加权网络。在我们的模型中,网络通过拓扑增长以及权重变化来进化。此外,我们引入了加权重连系数,它推广了拓扑网络的重连系数,以衡量两个相似度的顶点之间有一个高权重链接的趋势。我们的模型生成的网络表现出无标度行为与可调指数。此外,一些非平凡的功能,在现实世界中的网络中发现的再现,通过改变参数统治的重量演变的速度。最重要的是,通过对加权互变性系数的研究,我们发现由我们的模型生成的拓扑互变性网络和歧化网络实际上都是加权互变性的。

英文摘要:

Real-world networks process structured connections since they have non-trivial vertex degree correlation and clustering. Here we propose a toy model of structure formation in real-world weighted network. In our model, a network evolves by topological growth as well as by weight change. In addition, we introduce the weighted assortativity coefficient, which generalizes the assortativity coefficient of a topological network, to measure the tendency of having a high-weighted link between two vertices of similar degrees. Network generated by our model exhibits scale-free behavior with a tunable exponent. Besides, a few non-trivial features found in real-world networks are reproduced by varying the parameter ruling the speed of weight evolution. Most importantly, by studying the weighted assortativity coefficient, we found that both topologically assortative and disassortative networks generated by our model are in fact weighted assortative.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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