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3. Artigo de Periódico

Tipo:	Artigo de Periódico
Título:	Quantification of network structural dissimilarities
Autor(es):	Tiago Alves Schieber de Jesus Laura Carpi Albert Dıaz-Guilera Panos M. Pardalos Cristina Masoller Martın G. Ravetti
Resumen:	Identifying and quantifying dissimilarities among graphs is a fundamental and challenging problem of practical importance in many fields of science. Current methods of network comparison are limited to extract only partial information or are computationally very demanding. Here we propose an efficient and precise measure for network comparison, which is based on quantifying differences among distance probability distributions extracted from the networks. Extensive experiments on synthetic and real-world networks show that this measure returns non-zero values only when the graphs are non-isomorphic. Most importantly, the measure proposed here can identify and quantify structural topological differences that have a practical impact on the information flow through the network, such as the presence or absence of critical links that connect or disconnect connected components.
Asunto:	Administração de empresas
Idioma:	eng
País:	Brasil
Editor:	Universidade Federal de Minas Gerais
Sigla da Institución:	UFMG
Departamento:	FCE - DEPARTAMENTO DE CIÊNCIAS ADMINISTRATIVAS ICX - DEPARTAMENTO DE CIÊNCIA DA COMPUTAÇÃO
Tipo de acceso:	Acesso Aberto
Identificador DOI:	10.1038/ncomms13928
URI:	http://hdl.handle.net/1843/49833
Fecha del documento:	2017
metadata.dc.url.externa:	http://www.nature.com/articles/ncomms13928doi:10.1038/ncomms13928
Aparece en las colecciones:	Artigo de Periódico

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