Detection of community structures in networks via global optimization

Autores
Medus, Andrés Daniel; Acuña, G.; Dorso, Claudio Oscar
Año de publicación
2005
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
We present an analysis of communality structure in networks based on the application of simulated annealing techniques. In this case we use as "cost function" the already introduced modularity Q (1), which is based on the relative number of links within a commune against the number of links that would correspond in case the links were distributed randomly. We compare the results of our approach against other methodologies based on betweenness analysis and show that in all cases a better community structure can be attained. © 2005 Elsevier B.V. All rights reserved.
Fil: Medus, Andrés Daniel. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina
Fil: Acuña, G.. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina
Fil: Dorso, Claudio Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
Materia
BETWEENNESS
COMMUNALITY
NETWORKS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/73167
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Detection of community structures in networks via global optimizationMedus, Andrés DanielAcuña, G.Dorso, Claudio OscarBETWEENNESSCOMMUNALITYNETWORKShttps://purl.org/becyt/ford/1.3https://purl.org/becyt/ford/1We present an analysis of communality structure in networks based on the application of simulated annealing techniques. In this case we use as "cost function" the already introduced modularity Q (1), which is based on the relative number of links within a commune against the number of links that would correspond in case the links were distributed randomly. We compare the results of our approach against other methodologies based on betweenness analysis and show that in all cases a better community structure can be attained. © 2005 Elsevier B.V. All rights reserved.Fil: Medus, Andrés Daniel. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Acuña, G.. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Dorso, Claudio Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaElsevier Science2005-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/73167Medus, Andrés Daniel; Acuña, G.; Dorso, Claudio Oscar; Detection of community structures in networks via global optimization; Elsevier Science; Physica A: Statistical Mechanics and its Applications; 358; 2-4; 12-2005; 593-6040378-4371CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.physa.2005.04.022info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0378437105003973info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T11:51:58Zoai:ri.conicet.gov.ar:11336/73167instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-22 11:51:59.105CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Detection of community structures in networks via global optimization
title Detection of community structures in networks via global optimization
spellingShingle Detection of community structures in networks via global optimization
Medus, Andrés Daniel
BETWEENNESS
COMMUNALITY
NETWORKS
title_short Detection of community structures in networks via global optimization
title_full Detection of community structures in networks via global optimization
title_fullStr Detection of community structures in networks via global optimization
title_full_unstemmed Detection of community structures in networks via global optimization
title_sort Detection of community structures in networks via global optimization
dc.creator.none.fl_str_mv Medus, Andrés Daniel
Acuña, G.
Dorso, Claudio Oscar
author Medus, Andrés Daniel
author_facet Medus, Andrés Daniel
Acuña, G.
Dorso, Claudio Oscar
author_role author
author2 Acuña, G.
Dorso, Claudio Oscar
author2_role author
author
dc.subject.none.fl_str_mv BETWEENNESS
COMMUNALITY
NETWORKS
topic BETWEENNESS
COMMUNALITY
NETWORKS
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.3
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv We present an analysis of communality structure in networks based on the application of simulated annealing techniques. In this case we use as "cost function" the already introduced modularity Q (1), which is based on the relative number of links within a commune against the number of links that would correspond in case the links were distributed randomly. We compare the results of our approach against other methodologies based on betweenness analysis and show that in all cases a better community structure can be attained. © 2005 Elsevier B.V. All rights reserved.
Fil: Medus, Andrés Daniel. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina
Fil: Acuña, G.. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina
Fil: Dorso, Claudio Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
description We present an analysis of communality structure in networks based on the application of simulated annealing techniques. In this case we use as "cost function" the already introduced modularity Q (1), which is based on the relative number of links within a commune against the number of links that would correspond in case the links were distributed randomly. We compare the results of our approach against other methodologies based on betweenness analysis and show that in all cases a better community structure can be attained. © 2005 Elsevier B.V. All rights reserved.
publishDate 2005
dc.date.none.fl_str_mv 2005-12
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/73167
Medus, Andrés Daniel; Acuña, G.; Dorso, Claudio Oscar; Detection of community structures in networks via global optimization; Elsevier Science; Physica A: Statistical Mechanics and its Applications; 358; 2-4; 12-2005; 593-604
0378-4371
CONICET Digital
CONICET
url http://hdl.handle.net/11336/73167
identifier_str_mv Medus, Andrés Daniel; Acuña, G.; Dorso, Claudio Oscar; Detection of community structures in networks via global optimization; Elsevier Science; Physica A: Statistical Mechanics and its Applications; 358; 2-4; 12-2005; 593-604
0378-4371
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.physa.2005.04.022
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0378437105003973
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Science
publisher.none.fl_str_mv Elsevier Science
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1846782209255538688
score 12.982451

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