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Matrix growth models based on centrality measures: a first analysis

dc.contributor.authorPedroche, F.
dc.contributor.authorCriado, R.
dc.contributor.authorGarcia, E.
dc.contributor.authorRomance, M.
dc.date.accessioned2011-11-14T09:11:59Z
dc.date.available2011-11-14T09:11:59Z
dc.date.issued2011-10-24
dc.identifier.citationInt.J.Comp.Syst.Sci. vol.1(2), pp.124-128 (2011)es
dc.identifier.issn2174-6036
dc.identifier.urihttp://hdl.handle.net/10115/5745
dc.description.abstractA general growth model of random networks based on centrality measures is introduced. This formalism extends the well-known models of prefer- ential attachment. We propose to set the preferential attachment using a linear function of some centrality measures ranging from local to global scale. The aim is to include spectral measures, such as PageRank and Bonacich, and geodesic measures, such as betweenness and closeness. In this paper we present a first analysis using degree and Personalized PageRank.es
dc.language.isoenges
dc.publisherYamir Moreno. Universidad Rey Juan Carlos/ Regino Criado. Universidad Rey Juan Carloses
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subjectGrowing networkses
dc.subjectPageRankes
dc.subjectIn-Degreees
dc.titleMatrix growth models based on centrality measures: a first analysises
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.subject.unesco3304 Tecnología de Los Ordenadoreses
dc.subject.unesco12 Matemáticases
dc.description.departamentoMatemática Aplicada


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