It is very important to identify the important nodes in the network. On the basis of K-shell algorithm, this study studied the recognition of important nodes in complex networks. Firstly, this study introduced concepts of edge weight and influence coefficient, designed an IKS algorithm, and analyzed its recognition effect in Zachary network and real micro blog network. It was found from the experimental results that the partition results of the K-shell algorithm were coarse, while the partition results of the IKS algorithm were refined; the IKS algorithm could sort the important nodes accurately on the basis of the K-shell algorithm, and its rationality was higher than that of closeness centralization and PaperRank algorithm. The partition results in microblog network also verified the effectiveness of the improved method. The experimental results show that the IKS algorithm is reliable in the important node identification, which makes some contributions to the recognition of important nodes in complex network.

中文翻译：

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复杂网络重要节点识别算法研究

识别网络中的重要节点非常重要。本研究基于K-shell算法，研究了复杂网络中重要节点的识别问题。本研究首先引入了边缘权重和影响系数的概念，设计了IKS算法，并分析了其在Zachary网络和真实微博网络中的识别效果。从实验结果发现，K-shell算法的划分结果比较粗糙，而IKS算法的划分结果是细化的；IKS算法可以在K-shell算法的基础上对重要节点进行准确排序，其合理性高于接近中心化和PaperRank算法。微博网络中的划分结果也验证了改进方法的有效性。