Leveraging semantic similarity for folksonomy-based recommendation

Autores
Godoy, Daniela Lis; Rodriguez, Gustavo; Scavuzzo, Franco
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
For recommending interesting resources, such as Web pages or pictures available in social tagging systems, assessing their similarity with user profiles is crucial. Here, we analyze the role of semantic similarity to calculate the resemblance between user profiles and published resources in folksonomies. Experiments carried out with data from two social sites showed that associating semantics to tags results in more accurate similarities among elements in tagging systems and, consequently, enhances recommendations.
Fil: Godoy, Daniela Lis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina
Fil: Rodriguez, Gustavo. Universidad Nacional del Centro de la Provincia de Buenos Aires; Argentina
Fil: Scavuzzo, Franco. Universidad Nacional del Centro de la Provincia de Buenos Aires; Argentina
Materia
Social Tagging Systems
Folksonomies
Similarity Measures
Recommender Systems
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:11336/6786
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Leveraging semantic similarity for folksonomy-based recommendationGodoy, Daniela LisRodriguez, GustavoScavuzzo, FrancoSocial Tagging SystemsFolksonomiesSimilarity MeasuresRecommender Systemshttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1For recommending interesting resources, such as Web pages or pictures available in social tagging systems, assessing their similarity with user profiles is crucial. Here, we analyze the role of semantic similarity to calculate the resemblance between user profiles and published resources in folksonomies. Experiments carried out with data from two social sites showed that associating semantics to tags results in more accurate similarities among elements in tagging systems and, consequently, enhances recommendations.Fil: Godoy, Daniela Lis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; ArgentinaFil: Rodriguez, Gustavo. Universidad Nacional del Centro de la Provincia de Buenos Aires; ArgentinaFil: Scavuzzo, Franco. Universidad Nacional del Centro de la Provincia de Buenos Aires; ArgentinaInstitute of Electrical and Electronics Engineers2014-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/6786Godoy, Daniela Lis; Rodriguez, Gustavo; Scavuzzo, Franco; Leveraging semantic similarity for folksonomy-based recommendation; Institute of Electrical and Electronics Engineers; IEEE Internet Computing; 18; 1; 1-2014; 48-551089-7801enginfo:eu-repo/semantics/altIdentifier/url/http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6449234&tag=1info:eu-repo/semantics/altIdentifier/url/https://www.computer.org/csdl/mags/ic/2014/01/mic2014010048.pdfinfo:eu-repo/semantics/altIdentifier/doi/10.1109/MIC.2013.26info:eu-repo/semantics/altIdentifier/doi/info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T14:22:20Zoai:ri.conicet.gov.ar:11336/6786instacron: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:34982025-10-15 14:22:21.247CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Leveraging semantic similarity for folksonomy-based recommendation
title Leveraging semantic similarity for folksonomy-based recommendation
spellingShingle Leveraging semantic similarity for folksonomy-based recommendation
Godoy, Daniela Lis
Social Tagging Systems
Folksonomies
Similarity Measures
Recommender Systems
title_short Leveraging semantic similarity for folksonomy-based recommendation
title_full Leveraging semantic similarity for folksonomy-based recommendation
title_fullStr Leveraging semantic similarity for folksonomy-based recommendation
title_full_unstemmed Leveraging semantic similarity for folksonomy-based recommendation
title_sort Leveraging semantic similarity for folksonomy-based recommendation
dc.creator.none.fl_str_mv Godoy, Daniela Lis
Rodriguez, Gustavo
Scavuzzo, Franco
author Godoy, Daniela Lis
author_facet Godoy, Daniela Lis
Rodriguez, Gustavo
Scavuzzo, Franco
author_role author
author2 Rodriguez, Gustavo
Scavuzzo, Franco
author2_role author
author
dc.subject.none.fl_str_mv Social Tagging Systems
Folksonomies
Similarity Measures
Recommender Systems
topic Social Tagging Systems
Folksonomies
Similarity Measures
Recommender Systems
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv For recommending interesting resources, such as Web pages or pictures available in social tagging systems, assessing their similarity with user profiles is crucial. Here, we analyze the role of semantic similarity to calculate the resemblance between user profiles and published resources in folksonomies. Experiments carried out with data from two social sites showed that associating semantics to tags results in more accurate similarities among elements in tagging systems and, consequently, enhances recommendations.
Fil: Godoy, Daniela Lis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina
Fil: Rodriguez, Gustavo. Universidad Nacional del Centro de la Provincia de Buenos Aires; Argentina
Fil: Scavuzzo, Franco. Universidad Nacional del Centro de la Provincia de Buenos Aires; Argentina
description For recommending interesting resources, such as Web pages or pictures available in social tagging systems, assessing their similarity with user profiles is crucial. Here, we analyze the role of semantic similarity to calculate the resemblance between user profiles and published resources in folksonomies. Experiments carried out with data from two social sites showed that associating semantics to tags results in more accurate similarities among elements in tagging systems and, consequently, enhances recommendations.
publishDate 2014
dc.date.none.fl_str_mv 2014-01
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/11336/6786
Godoy, Daniela Lis; Rodriguez, Gustavo; Scavuzzo, Franco; Leveraging semantic similarity for folksonomy-based recommendation; Institute of Electrical and Electronics Engineers; IEEE Internet Computing; 18; 1; 1-2014; 48-55
1089-7801
url http://hdl.handle.net/11336/6786
identifier_str_mv Godoy, Daniela Lis; Rodriguez, Gustavo; Scavuzzo, Franco; Leveraging semantic similarity for folksonomy-based recommendation; Institute of Electrical and Electronics Engineers; IEEE Internet Computing; 18; 1; 1-2014; 48-55
1089-7801
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6449234&tag=1
info:eu-repo/semantics/altIdentifier/url/https://www.computer.org/csdl/mags/ic/2014/01/mic2014010048.pdf
info:eu-repo/semantics/altIdentifier/doi/10.1109/MIC.2013.26
info:eu-repo/semantics/altIdentifier/doi/
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 Institute of Electrical and Electronics Engineers
publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers
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_ 1846082622274404352
score 13.22299

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