Quantification of network structural dissimilarities

Identifying and quantifying dissimilarities among graphs is a problem of practical importance, but current approaches are either limited or computationally demanding. Here, the authors propose an efficiently computable measure for network comparison that can identify structural topological differenc...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Tiago A. Schieber, Laura Carpi, Albert Díaz-Guilera, Panos M. Pardalos, Cristina Masoller, Martín G. Ravetti
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/9528b474f36f44a9a563164865c86acf
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:9528b474f36f44a9a563164865c86acf
record_format	dspace
spelling	oai:doaj.org-article:9528b474f36f44a9a563164865c86acf2021-12-02T15:38:38ZQuantification of network structural dissimilarities10.1038/ncomms139282041-1723https://doaj.org/article/9528b474f36f44a9a563164865c86acf2017-01-01T00:00:00Zhttps://doi.org/10.1038/ncomms13928https://doaj.org/toc/2041-1723Identifying and quantifying dissimilarities among graphs is a problem of practical importance, but current approaches are either limited or computationally demanding. Here, the authors propose an efficiently computable measure for network comparison that can identify structural topological differences.Tiago A. SchieberLaura CarpiAlbert Díaz-GuileraPanos M. PardalosCristina MasollerMartín G. RavettiNature PortfolioarticleScienceQENNature Communications, Vol 8, Iss 1, Pp 1-10 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Tiago A. Schieber Laura Carpi Albert Díaz-Guilera Panos M. Pardalos Cristina Masoller Martín G. Ravetti Quantification of network structural dissimilarities
description	Identifying and quantifying dissimilarities among graphs is a problem of practical importance, but current approaches are either limited or computationally demanding. Here, the authors propose an efficiently computable measure for network comparison that can identify structural topological differences.
format	article
author	Tiago A. Schieber Laura Carpi Albert Díaz-Guilera Panos M. Pardalos Cristina Masoller Martín G. Ravetti
author_facet	Tiago A. Schieber Laura Carpi Albert Díaz-Guilera Panos M. Pardalos Cristina Masoller Martín G. Ravetti
author_sort	Tiago A. Schieber
title	Quantification of network structural dissimilarities
title_short	Quantification of network structural dissimilarities
title_full	Quantification of network structural dissimilarities
title_fullStr	Quantification of network structural dissimilarities
title_full_unstemmed	Quantification of network structural dissimilarities
title_sort	quantification of network structural dissimilarities
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/9528b474f36f44a9a563164865c86acf
work_keys_str_mv	AT tiagoaschieber quantificationofnetworkstructuraldissimilarities AT lauracarpi quantificationofnetworkstructuraldissimilarities AT albertdiazguilera quantificationofnetworkstructuraldissimilarities AT panosmpardalos quantificationofnetworkstructuraldissimilarities AT cristinamasoller quantificationofnetworkstructuraldissimilarities AT martingravetti quantificationofnetworkstructuraldissimilarities
_version_	1718386127369404416

Quantification of network structural dissimilarities

Ejemplares similares