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Locating the propagation source in complex networks with observers-based similarity measures and direction-induced search

Locating the propagation source is one of the most important strategies to control the harmful diffusion process on complex networks. Most existing methods only consider the infection time information of the observers, but the diffusion direction information of the observers is ignored, which is hel...

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Autores principales: Yang, Fan, Li, Chungui, Peng, Yong, Liu, Jingxian, Yao, Yabing, Wen, Jiayan, Yang, Shuhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10072820/
https://www.ncbi.nlm.nih.gov/pubmed/37362267
http://dx.doi.org/10.1007/s00500-023-08000-7
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author Yang, Fan
Li, Chungui
Peng, Yong
Liu, Jingxian
Yao, Yabing
Wen, Jiayan
Yang, Shuhong
author_facet Yang, Fan
Li, Chungui
Peng, Yong
Liu, Jingxian
Yao, Yabing
Wen, Jiayan
Yang, Shuhong
author_sort Yang, Fan
collection PubMed
description Locating the propagation source is one of the most important strategies to control the harmful diffusion process on complex networks. Most existing methods only consider the infection time information of the observers, but the diffusion direction information of the observers is ignored, which is helpful to locate the source. In this paper, we consider both of the diffusion direction information and the infection time information to locate the source. We introduce a relaxed direction-induced search (DIS) to utilize the diffusion direction information of the observers to approximate the actual diffusion tree on a network. Based on the relaxed DIS, we further utilize the infection time information of the observers to define two kinds of observers-based similarity measures, including the Infection Time Similarity and the Infection Time Order Similarity. With the two kinds of similarity measures and the relaxed DIS, a novel source locating method is proposed. We validate the performance of the proposed method on a series of synthetic and real networks. The experimental results show that the proposed method is feasible and effective in accurately locating the propagation source.
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spelling pubmed-100728202023-04-05 Locating the propagation source in complex networks with observers-based similarity measures and direction-induced search Yang, Fan Li, Chungui Peng, Yong Liu, Jingxian Yao, Yabing Wen, Jiayan Yang, Shuhong Soft comput Application of Soft Computing Locating the propagation source is one of the most important strategies to control the harmful diffusion process on complex networks. Most existing methods only consider the infection time information of the observers, but the diffusion direction information of the observers is ignored, which is helpful to locate the source. In this paper, we consider both of the diffusion direction information and the infection time information to locate the source. We introduce a relaxed direction-induced search (DIS) to utilize the diffusion direction information of the observers to approximate the actual diffusion tree on a network. Based on the relaxed DIS, we further utilize the infection time information of the observers to define two kinds of observers-based similarity measures, including the Infection Time Similarity and the Infection Time Order Similarity. With the two kinds of similarity measures and the relaxed DIS, a novel source locating method is proposed. We validate the performance of the proposed method on a series of synthetic and real networks. The experimental results show that the proposed method is feasible and effective in accurately locating the propagation source. Springer Berlin Heidelberg 2023-04-04 /pmc/articles/PMC10072820/ /pubmed/37362267 http://dx.doi.org/10.1007/s00500-023-08000-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Application of Soft Computing
Yang, Fan
Li, Chungui
Peng, Yong
Liu, Jingxian
Yao, Yabing
Wen, Jiayan
Yang, Shuhong
Locating the propagation source in complex networks with observers-based similarity measures and direction-induced search
title Locating the propagation source in complex networks with observers-based similarity measures and direction-induced search
title_full Locating the propagation source in complex networks with observers-based similarity measures and direction-induced search
title_fullStr Locating the propagation source in complex networks with observers-based similarity measures and direction-induced search
title_full_unstemmed Locating the propagation source in complex networks with observers-based similarity measures and direction-induced search
title_short Locating the propagation source in complex networks with observers-based similarity measures and direction-induced search
title_sort locating the propagation source in complex networks with observers-based similarity measures and direction-induced search
topic Application of Soft Computing
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10072820/
https://www.ncbi.nlm.nih.gov/pubmed/37362267
http://dx.doi.org/10.1007/s00500-023-08000-7
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