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Identifying key nodes based on improved structural holes in complex networks

机译:基于复杂网络中改进的结构孔来识别关键节点

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Identifying key nodes in complex networks is of theoretical and practical significance. Local metrics such as degree centrality is simplest but cannot effectively identify the important bridging nodes. Global metrics such as betweenness and closeness centrality can better identify important nodes, but they are often restricted by the unknown topology and cannot be conveniently applied in large-scale networks. In this paper, we propose an effective ranking method based on an Improved Structural Holes (ISH) to identify the important nodes. ISH method only uses the degree of nodes and the nearest neighborhood information rather than considering the global structure of a network. Our experimental results on five complex networks show that the proposed method can effectively identify the key nodes in complex networks and can also be applied in large-scale or unconnected networks. (C) 2017 Elsevier B.V. All rights reserved.
机译:识别复杂网络中的关键节点是理论和实际意义。 诸如程度中心的本地度量是最简单的,但不能有效地识别重要的桥接节点。 诸如之间的全球度量和接近中心之间可以更好地识别重要节点,但它们通常受到未知拓扑的限制,并且不能方便地应用于大型网络。 在本文中,我们提出了一种基于改进的结构孔(ISH)来识别重要节点的有效排名方法。 ISH方法仅使用节点和最近的邻域信息,而不是考虑网络的全局结构。 我们在五个复杂网络上的实验结果表明,该方法可以有效地识别复杂网络中的关键节点,也可以以大规模或未连接的网络应用。 (c)2017年Elsevier B.V.保留所有权利。

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