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Global Recursive Based Node Importance Evaluation

机译:基于全局递归的节点重要性评估

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The world city network (WCN) research has been promoting the evaluation algorithms in complex networks. The study of urban network focuses on the measurements of city position in the WCN. In previous study, a set of algorithms such as centricity evaluation, power evaluation and their recursive power are proposed to support the WCN research. In this paper, we propose a novel global recursive based node importance evaluation (GRNIE) algorithm for WCN, which improves the performance in evaluating the network centricity and power by being applied to the Friedmann Basics Network. The results of the experiment show that the proposed GRNIE outperforms the previous algorithms (i.e., degree, recursive centricity, recursive power) in task of classification with the improvements of 72 %, 32 % and 20 % respectively in accuracy.
机译:世界城市网络(WCN)的研究一直在促进复杂网络中的评估算法。城市网络的研究集中在WCN中城市位置的测量。在先前的研究中,提出了一组算法,如中心性评估,功效评估及其递归功效,以支持WCN研究。在本文中,我们提出了一种新颖的基于WCN的全局递归基于节点重要性评估(GRNIE)算法,该算法通过应用于Friedmann Basics网络,提高了评估网络中心性和功率的性能。实验结果表明,提出的GRNIE在分类任务上优于以前的算法(即度,递归中心性,递归能力),准确率分别提高了72%,32%和20%。

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