| 摘 要: k-核分解算法是一种优秀的评估复杂网络节点重要性的方法，然而该方法对于复杂网络节点的排序还存 在一些问题。本文提出了一种改进的加权k-核分解算法，通过改进节点加权度的计算对已提出的方法进行改进。然后 在四个真实网络上利用SIR传染病模型进行了实验仿真。实验结果表明，改进后的算法比原有方法在评估节点重要性方 面更具有优越性。 |
| 关键词: 复杂网络；节点重要度；k-核分解；SIR |
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中图分类号: TP393.0
文献标识码: A
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| A New Improved Weighted K-shell Decomposition Method |
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SONG Qichao
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( School of Computer and Information Science, Southwest University, Chongqing 400715, China)
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| Abstract: K-shell decomposition is an excellent method in evaluating the nodes influence of complex network. While this method is not perfect in sorting the nodes importance of complex network.In this paper,an improved weighted k-shell decompositionis proposed.This method improved the method of calculating nodes weight.To evaluate the improved method, we did some experiment using SIR disease spreading model in four real networks.The experiment results show that the improved method is prior to the existing method in evaluating nodes influence. |
| Keywords: complex network;nodes influence;k-shell decomposition;SIR |
