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Evaluating importance of nodes in complex networks with local volume information dimension

arXiv 2111.13585 ↗First posted 23 Nov 2021cs.SI cs.AIcited by 0

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Abstract (arXiv)

How to evaluate the importance of nodes is essential in research of complex network. There are many methods proposed for solving this problem, but they still have room to be improved. In this paper, a new approach called local volume information dimension is proposed. In this method, the sum of degree of nodes within different distances of central node is calculated. The information within the certain distance is described by the information entropy. Compared to other methods, the proposed method considers the information of the nodes from different distances more comprehensively. For the purpose of showing the effectiveness of the proposed method, experiments on real-world networks are implemented. Promising results indicate the effectiveness of the proposed method.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 37 references that are in the map. First posted on arXiv 23 Nov 2021.

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References · 3

  1. 2017Influence maximization by rumor spreading on correlated networks through community identificationcited by 3
  2. 2020The Fractional Preferential Attachment Scale-Free Network Modelcited by 3
  3. 2021A Fast Evidential Approach for Stock Forecastingcited by 2

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