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复杂网络中的有影响力节点识别:全面的文献综述

Influential nodes identification in complex networks: a comprehensive literature review.

作者信息

Ait Rai Khaoula, Machkour Mustapha, Antari Jilali

机构信息

Computer System and Vision Laboratory, Faculty of Sciences Agadir BP8106, Ibn Zohr University, Agadir, Morocco.

Laboratory of Computer Systems Engineering, Mathematics and Applications, Polydisciplinary Faculty of Taroudant, Ibn Zohr University, B.P. 8106, Agadir, Morocco.

出版信息

Beni Suef Univ J Basic Appl Sci. 2023;12(1):18. doi: 10.1186/s43088-023-00357-w. Epub 2023 Feb 14.

DOI:10.1186/s43088-023-00357-w
PMID:36819294
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9927061/
Abstract

Researchers have paid a lot of attention to complex networks in recent decades. Due to their rapid evolution, they turn into a major scientific and innovative field. Several studies on complex networks are carried out, and other subjects are evolving every day such as the challenge of detecting influential nodes. In this study, we provide a brief overview of complex networks, as well as several concepts key related to measurements, the structure of complex network and social influence, an important state of the art on complex networks including basic metrics on complex networks, the evolution of their topology over the years as well as the dynamic of networks. A detailed literature about influential finding approaches is also provided to indicate their strength and shortcomings. We aim that our contribution of literature can be an interesting base of information for beginners' scientists in this field. At the end of this paper, some conclusions are drawn and some future perspectives are mentioned to be studied as new directions in the future. More detailed references are provided to go further and deep in this area.

摘要

近几十年来,研究人员对复杂网络给予了极大关注。由于其快速发展,复杂网络已成为一个重要的科学与创新领域。人们开展了多项关于复杂网络的研究,并且其他相关主题也在不断发展,比如检测有影响力节点的挑战。在本研究中,我们简要概述了复杂网络,以及一些与测量、复杂网络结构和社会影响相关的关键概念,介绍了复杂网络领域的重要技术现状,包括复杂网络的基本指标、其拓扑结构多年来的演变以及网络动态。我们还提供了关于有影响力节点发现方法的详细文献,以指出其优缺点。我们希望我们的文献贡献能够为该领域的新手科学家提供一个有趣的信息基础。在本文结尾,得出了一些结论,并提及了一些未来展望,作为未来的新研究方向。还提供了更详细的参考文献,以便在该领域进行更深入的研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/feed/9927061/f86597d2956a/43088_2023_357_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/feed/9927061/e02b21ce6212/43088_2023_357_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/feed/9927061/f86597d2956a/43088_2023_357_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/feed/9927061/e02b21ce6212/43088_2023_357_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/feed/9927061/f86597d2956a/43088_2023_357_Fig2_HTML.jpg

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