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Subgraph centrality and clustering in complex hyper-networks

机译:复杂超网络中的子图集中度和聚类

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摘要

The representation of complex systems as networks is inappropriate for the study of certain problems. We show several examples of social, biological, ecological and technological systems where the use of complex networks gives very limited information about the structure of the system. Consequently, we extend the concepts of subgraph centrality and clustering for complex networks represented by hypergraphs: complex hyper-networks. The first parameter characterizes the node participation in different sub-hypergraphs and the second one characterizes the transitivity in the hyper-network through the proportion of hyper-triangles to paths of length two. Another measure characterizing the formation of triples of mutually adjacent groups in the hyper-network is also introduced. All of these characteristics are studied in three different hyper-networks: a scientific collaboration hyper-network, an ecological competition hyper-network and the hyper-network formed by the American corporate elite in 1999. (c) 2006 Elsevier B.V. All rights reserved.
机译:将复杂系统表示为网络不适用于某些问题的研究。我们展示了一些社会,生物,生态和技术系统的示例,其中使用复杂的网络只能提供有关系统结构的非常有限的信息。因此,我们扩展了以超图表示的复杂网络的子图集中性和聚类的概念:复杂超网络。第一个参数表征节点参与不同的子超图中,第二个参数表征超网络中超三角形在长度为2的路径中所占的比例。还介绍了表征超网络中相互邻近的基团的三元组的形成的另一种措施。在三个不同的超网络中研究了所有这些特征:科学协作超网络,生态竞争超网络和由美国企业精英于1999年形成的超网络。(c)2006 Elsevier B.V.保留所有权利。

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