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Community Detection in Scale-Free Networks Based on Hypergraph Model

机译:基于超图模型的无标度网络社区检测

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摘要

The investigation of community structures in networks is an important issue in many domains and disciplines. There have been considerable recent interest algorithms for finding communities in networks. In this paper we present a method of detecting community structure based on hypergraph model. The hypergraph model maps the relationship in the original data into a hypergraph. A hyperedge represents a relationship among subsets of data and the weight of the hyperedge reflects the strength of this affinity. We assign the density of a hyperedge to its weight. We present and illustrate the results of experiments on the Enron data set. These experiments demonstrate that our approach is applicable and effective.
机译:在许多领域和学科中,对网络中社区结构的调查是一个重要问题。最近有相当大的兴趣算法可以找到网络中的社区。本文提出了一种基于超图模型的社区结构检测方法。超图模型将原始数据中的关系映射到一个超图中。超边缘代表数据子集之间的关系,超边缘的权重反映了这种亲和力的强度。我们将超边的密度分配给它的权重。我们介绍并说明了在安然数据集上的实验结果。这些实验证明我们的方法是适用和有效的。

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