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Node Importance based Label Propagation Algorithm for overlapping community detection in networks

机译:基于节点重要性标签传播算法在网络中重叠社区检测

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The enormous growth of the Web led to the birth of different network structures. Therefore, one of the important issues in the field of complex network analysis is to find and exploit the structure. Many studies have been carried out in this sense. The Label Propagation Algorithm (LPA) is among the most recognized approaches to detect disjointed communities. It is a simple and fast method, but its major disadvantage lies in its instability due to a random update. In this paper, we introduce a Node Importance based Label Propagation Algorithm (NI-LPA), a new algorithm for detecting overlapping communities in networks. As indicated in its name, NI-LPA is an improved version of LPA which maintains its simplicity and enhances its accuracy. In fact, we adopt the LPA strategy to allow a node to contain a set of labels. Moreover, the algorithm simulates a special propagation and filtering process using information deduced from the properties of nodes. Experimental results on artificial and real-world networks with different sizes, complexities and densities show the efficiency of our approach to detect overlapping communities. (C) 2019 Elsevier Ltd. All rights reserved.
机译:网络的巨大增长导致了不同网络结构的诞生。因此,复杂网络分析领域中的一个重要问题是找到和利用结构。在这个意义上进行了许多研究。标签传播算法(LPA)是检测脱位社区的最识别的方法之一。这是一种简单快速的方法,但由于随机更新,其主要缺点在于其不稳定性。在本文中,我们介绍了一种基于节点重要的标签传播算法(NI-LPA),一种用于检测网络中的重叠社区的新算法。如其名称所示,Ni-LPA是LPA的改进版本,其保持其简单性并提高其准确性。实际上,我们采用LPA策略来允许节点包含一组标签。此外,该算法使用从节点的属性推断的信息来模拟特殊的传播和过滤过程。具有不同尺寸,复杂性和密度的人工和真实网络的实验结果表明了我们检测重叠社区的方法的效率。 (c)2019 Elsevier Ltd.保留所有权利。

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