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The node importance in actual complex networks based on a multi-attribute ranking method

机译:基于多属性排序方法的实际复杂网络中的节点重要性

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This paper addresses the problem of evaluating the node importance in actual complex networks. Firstly, the indicators used to evaluate the node importance are defined based on complex network theory, and their characteristics are analyzed in detail. Besides, a new indicator is put forward on the basis of K-shell decomposition, named improved K-shell. Secondly, in order to evaluate the node importance comprehensively, a multi-attribute ranking method is proposed based on the Technique for Order Preference by Similarity to Ideal Object (TOPSIS). Finally, our method is used to study two actual cases. Results show that, our method outperforms other methods in distinguishing the node importance of actual complex networks and can provide scientific decision support for the administration department. (C) 2015 Elsevier B.V. All rights reserved.
机译:本文解决了在实际复杂网络中评估节点重要性的问题。首先,基于复杂网络理论定义了评价节点重要性的指标,并对其特性进行了详细分析。此外,在K-shell分解的基础上提出了一种新的指标,即改进的K-shell。其次,为了全面评价节点的重要性,提出了一种基于理想对象相似度的顺序偏好技术的多属性排序方法。最后,我们的方法用于研究两个实际案例。结果表明,该方法在区分实际复杂网络的节点重要性方面优于其他方法,可以为管理部门提供科学的决策支持。 (C)2015 Elsevier B.V.保留所有权利。

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