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一种基于K-Shell的复杂网络重要节点发现算法

Computer Technology and Development(2015)

Cited 13|Views2
Abstract
复杂网络中的重要节点通常数量较少,但是对网络的影响却很大。为了能够有效地发现网络拓扑结构中的重要节点,文中基于K -Shell算法,在考虑节点自身重要度的基础上,考虑了邻居节点对自身节点的重要度贡献,提出KSA( K-Shell-Affect)算法。该算法引入影响度概念,用节点自身的K -Shell值和与对其邻居节点的影响度来表征其对邻居节点的重要度贡献。对具有明显社团结构的Zachary网络进行仿真表明,该算法可行有效,克服了K - Shell划分结果的粗粒化,能够正确找到网络中的重要节点,具有一定的合理性,尤其在具有社团结构的网络中,能够十分有效地找到社团内部的核心节点。
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