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Research on the Node Importance of a Weighted Network Based on the K-Order Propagation Number Algorithm

To describe both the global and local characteristics of a network more comprehensively, we propose the weighted K-order propagation number (WKPN) algorithm to extract the disease propagation based on the network topology to evaluate the node importance. Each node is set as the source of infection,...

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Autores principales: Tang, Pingchuan, Song, Chuancheng, Ding, Weiwei, Ma, Junkai, Dong, Jun, Huang, Liya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516838/
https://www.ncbi.nlm.nih.gov/pubmed/33286138
http://dx.doi.org/10.3390/e22030364
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author Tang, Pingchuan
Song, Chuancheng
Ding, Weiwei
Ma, Junkai
Dong, Jun
Huang, Liya
author_facet Tang, Pingchuan
Song, Chuancheng
Ding, Weiwei
Ma, Junkai
Dong, Jun
Huang, Liya
author_sort Tang, Pingchuan
collection PubMed
description To describe both the global and local characteristics of a network more comprehensively, we propose the weighted K-order propagation number (WKPN) algorithm to extract the disease propagation based on the network topology to evaluate the node importance. Each node is set as the source of infection, and the total number of infected nodes is defined as the K-order propagation number after experiencing the propagation time K. The simulation of the symmetric network with bridge nodes indicated that the WKPN algorithm was more effective for evaluation of the algorithm features. A deliberate attack strategy, which indicated an attack on the network according to the node importance from high to low, was employed to evaluate the WKPN algorithm in real networks. Compared with the other methods tested, the results demonstrate the applicability and advancement that a lower number of nodes, with a higher importance calculated by the K-order propagation number algorithm, has to achieve full damage to the network structure.
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spelling pubmed-75168382020-11-09 Research on the Node Importance of a Weighted Network Based on the K-Order Propagation Number Algorithm Tang, Pingchuan Song, Chuancheng Ding, Weiwei Ma, Junkai Dong, Jun Huang, Liya Entropy (Basel) Article To describe both the global and local characteristics of a network more comprehensively, we propose the weighted K-order propagation number (WKPN) algorithm to extract the disease propagation based on the network topology to evaluate the node importance. Each node is set as the source of infection, and the total number of infected nodes is defined as the K-order propagation number after experiencing the propagation time K. The simulation of the symmetric network with bridge nodes indicated that the WKPN algorithm was more effective for evaluation of the algorithm features. A deliberate attack strategy, which indicated an attack on the network according to the node importance from high to low, was employed to evaluate the WKPN algorithm in real networks. Compared with the other methods tested, the results demonstrate the applicability and advancement that a lower number of nodes, with a higher importance calculated by the K-order propagation number algorithm, has to achieve full damage to the network structure. MDPI 2020-03-22 /pmc/articles/PMC7516838/ /pubmed/33286138 http://dx.doi.org/10.3390/e22030364 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Tang, Pingchuan
Song, Chuancheng
Ding, Weiwei
Ma, Junkai
Dong, Jun
Huang, Liya
Research on the Node Importance of a Weighted Network Based on the K-Order Propagation Number Algorithm
title Research on the Node Importance of a Weighted Network Based on the K-Order Propagation Number Algorithm
title_full Research on the Node Importance of a Weighted Network Based on the K-Order Propagation Number Algorithm
title_fullStr Research on the Node Importance of a Weighted Network Based on the K-Order Propagation Number Algorithm
title_full_unstemmed Research on the Node Importance of a Weighted Network Based on the K-Order Propagation Number Algorithm
title_short Research on the Node Importance of a Weighted Network Based on the K-Order Propagation Number Algorithm
title_sort research on the node importance of a weighted network based on the k-order propagation number algorithm
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516838/
https://www.ncbi.nlm.nih.gov/pubmed/33286138
http://dx.doi.org/10.3390/e22030364
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