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Structural identification of large statistically distributed vertex degree

机译:大统计分布顶点度的结构识别

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摘要

For the modeling of large networks a random graph is proposed, the generation of which is based on the use of nonlinear preferential attachment rule. The analytical solution for the vertex degree distribution is given as well as the method for the calibration of graph generator according to the node degree distributions in real networks. Possibilities of structural identification are demonstrated using the proposed graph for a network of actors acted the same films, the Internet, networks of roads, networks of complementary goods in online store.
机译:对于大型网络的建模,提出了一个随机图,该图的生成基于非线性优先依附规则的使用。根据实际网络中的节点度分布,给出了顶点度分布的解析解以及图生成器的标定方法。使用提议的图表,对于演员扮演相同电影的演员网络,互联网,道路网络,在线商店中的互补商品网络,证明了结构识别的可能性。

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