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Flexible model of network embedding
There has lately been increased interest in describing complex systems not merely as single networks but rather as collections of networks that are coupled to one another. We introduce an analytically tractable model that enables one to connect two layers in a multilayer network by controlling the l...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6691014/ https://www.ncbi.nlm.nih.gov/pubmed/31406298 http://dx.doi.org/10.1038/s41598-019-48217-x |
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author | Fernández-Gracia, Juan Onnela, Jukka-Pekka |
author_facet | Fernández-Gracia, Juan Onnela, Jukka-Pekka |
author_sort | Fernández-Gracia, Juan |
collection | PubMed |
description | There has lately been increased interest in describing complex systems not merely as single networks but rather as collections of networks that are coupled to one another. We introduce an analytically tractable model that enables one to connect two layers in a multilayer network by controlling the locality of coupling. In particular we introduce a tractable model for embedding one network (A) into another (B), focusing on the case where network A has many more nodes than network B. In our model, nodes in network A are assigned, or embedded, to the nodes in network B using an assignment rule where the extent of node localization is controlled by a single parameter. We start by mapping an unassigned “source” node in network A to a randomly chosen “target” node in network B. We then assign the neighbors of the source node to the neighborhood of the target node using a random walk starting at the target node and with a per-step stopping probability q. By varying the parameter q, we are able to produce a range of embeddings from local (q = 1) to global (q → 0). The simplicity of the model allows us to calculate key quantities, making it a useful starting point for more realistic models. |
format | Online Article Text |
id | pubmed-6691014 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-66910142019-08-15 Flexible model of network embedding Fernández-Gracia, Juan Onnela, Jukka-Pekka Sci Rep Article There has lately been increased interest in describing complex systems not merely as single networks but rather as collections of networks that are coupled to one another. We introduce an analytically tractable model that enables one to connect two layers in a multilayer network by controlling the locality of coupling. In particular we introduce a tractable model for embedding one network (A) into another (B), focusing on the case where network A has many more nodes than network B. In our model, nodes in network A are assigned, or embedded, to the nodes in network B using an assignment rule where the extent of node localization is controlled by a single parameter. We start by mapping an unassigned “source” node in network A to a randomly chosen “target” node in network B. We then assign the neighbors of the source node to the neighborhood of the target node using a random walk starting at the target node and with a per-step stopping probability q. By varying the parameter q, we are able to produce a range of embeddings from local (q = 1) to global (q → 0). The simplicity of the model allows us to calculate key quantities, making it a useful starting point for more realistic models. Nature Publishing Group UK 2019-08-12 /pmc/articles/PMC6691014/ /pubmed/31406298 http://dx.doi.org/10.1038/s41598-019-48217-x Text en © The Author(s) 2019 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Fernández-Gracia, Juan Onnela, Jukka-Pekka Flexible model of network embedding |
title | Flexible model of network embedding |
title_full | Flexible model of network embedding |
title_fullStr | Flexible model of network embedding |
title_full_unstemmed | Flexible model of network embedding |
title_short | Flexible model of network embedding |
title_sort | flexible model of network embedding |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6691014/ https://www.ncbi.nlm.nih.gov/pubmed/31406298 http://dx.doi.org/10.1038/s41598-019-48217-x |
work_keys_str_mv | AT fernandezgraciajuan flexiblemodelofnetworkembedding AT onnelajukkapekka flexiblemodelofnetworkembedding |