Node and edge nonlinear eigenvector centrality for hypergraphs

Evaluating the importance of nodes and hyperedges in hypergraphs is relevant to link detection, link prediction and matrix completion. Here, the authors define a family of nonlinear eigenvector centrality measures for both edges and nodes in hypergraphs, propose an algorithm to calculate them, and i...

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Detalles Bibliográficos
Autores principales:	Francesco Tudisco, Desmond J. Higham
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Astrophysics QB460-466 Physics QC1-999
Acceso en línea:	https://doaj.org/article/1223cb91ad414a9d8ddc81a142c1d18a
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id	oai:doaj.org-article:1223cb91ad414a9d8ddc81a142c1d18a
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spelling	oai:doaj.org-article:1223cb91ad414a9d8ddc81a142c1d18a2021-12-02T15:26:51ZNode and edge nonlinear eigenvector centrality for hypergraphs10.1038/s42005-021-00704-22399-3650https://doaj.org/article/1223cb91ad414a9d8ddc81a142c1d18a2021-09-01T00:00:00Zhttps://doi.org/10.1038/s42005-021-00704-2https://doaj.org/toc/2399-3650Evaluating the importance of nodes and hyperedges in hypergraphs is relevant to link detection, link prediction and matrix completion. Here, the authors define a family of nonlinear eigenvector centrality measures for both edges and nodes in hypergraphs, propose an algorithm to calculate them, and illustrate their application on real-world data sets.Francesco TudiscoDesmond J. HighamNature PortfolioarticleAstrophysicsQB460-466PhysicsQC1-999ENCommunications Physics, Vol 4, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Astrophysics QB460-466 Physics QC1-999
spellingShingle	Astrophysics QB460-466 Physics QC1-999 Francesco Tudisco Desmond J. Higham Node and edge nonlinear eigenvector centrality for hypergraphs
description	Evaluating the importance of nodes and hyperedges in hypergraphs is relevant to link detection, link prediction and matrix completion. Here, the authors define a family of nonlinear eigenvector centrality measures for both edges and nodes in hypergraphs, propose an algorithm to calculate them, and illustrate their application on real-world data sets.
format	article
author	Francesco Tudisco Desmond J. Higham
author_facet	Francesco Tudisco Desmond J. Higham
author_sort	Francesco Tudisco
title	Node and edge nonlinear eigenvector centrality for hypergraphs
title_short	Node and edge nonlinear eigenvector centrality for hypergraphs
title_full	Node and edge nonlinear eigenvector centrality for hypergraphs
title_fullStr	Node and edge nonlinear eigenvector centrality for hypergraphs
title_full_unstemmed	Node and edge nonlinear eigenvector centrality for hypergraphs
title_sort	node and edge nonlinear eigenvector centrality for hypergraphs
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/1223cb91ad414a9d8ddc81a142c1d18a
work_keys_str_mv	AT francescotudisco nodeandedgenonlineareigenvectorcentralityforhypergraphs AT desmondjhigham nodeandedgenonlineareigenvectorcentralityforhypergraphs
_version_	1718387186175311872

Node and edge nonlinear eigenvector centrality for hypergraphs

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