Semantic grounding of social annotations for enhancing resource classification in folksonomies

Autores
Tommasel, Antonela; Godoy, Daniela Lis
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
User-generated annotations in tagging or bookmarking sites such as Flickr or Delicious can provide a promising and interesting source of information for aiding tasks such as Web resource classification. However, the use of tags brings up some challenges. Since there are no constraints on the terms that can be used for tagging, noise and ambiguity are introduced when users annotate resources. Moreover, traditional bag-of-words representations ignore connections between terms and, thus, are affected by synonymity and hyponymia. Althougth tag-based representations are a valuable source for classifying resources, the problems associated with the unsupervised nature of tags may hinder classification results. This paper presents an approach for semantically analysing social annotations in order to attain enriched concept-based representations of Web resources. Representations are enriched with concepts extracted from WordNet and Wikipedia to overcome problems caused by natural language as well as enhancing the quality of information available for performing an effective classification of resources. Several strategies for tag pre-processing, concept disambiguation and incorporation of semantic entities to representations are discussed and evaluated in this paper. Experimental results showed that the strategies proposed to associate tags with conceptual entities allow improving resource classification results, outperforming traditional approaches based on bag-of-words representations.
Fil: Tommasel, Antonela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Fil: Godoy, Daniela Lis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Materia
Folksonomies
Resource Classification
Semantic-Based Representations
Social Tagging 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:11336/50677
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Semantic grounding of social annotations for enhancing resource classification in folksonomiesTommasel, AntonelaGodoy, Daniela LisFolksonomiesResource ClassificationSemantic-Based RepresentationsSocial Tagging Systemshttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1User-generated annotations in tagging or bookmarking sites such as Flickr or Delicious can provide a promising and interesting source of information for aiding tasks such as Web resource classification. However, the use of tags brings up some challenges. Since there are no constraints on the terms that can be used for tagging, noise and ambiguity are introduced when users annotate resources. Moreover, traditional bag-of-words representations ignore connections between terms and, thus, are affected by synonymity and hyponymia. Althougth tag-based representations are a valuable source for classifying resources, the problems associated with the unsupervised nature of tags may hinder classification results. This paper presents an approach for semantically analysing social annotations in order to attain enriched concept-based representations of Web resources. Representations are enriched with concepts extracted from WordNet and Wikipedia to overcome problems caused by natural language as well as enhancing the quality of information available for performing an effective classification of resources. Several strategies for tag pre-processing, concept disambiguation and incorporation of semantic entities to representations are discussed and evaluated in this paper. Experimental results showed that the strategies proposed to associate tags with conceptual entities allow improving resource classification results, outperforming traditional approaches based on bag-of-words representations.Fil: Tommasel, Antonela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; ArgentinaFil: Godoy, Daniela Lis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; ArgentinaSpringer2015-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/50677Tommasel, Antonela; Godoy, Daniela Lis; Semantic grounding of social annotations for enhancing resource classification in folksonomies; Springer; Journal Of Intelligent Information Systems; 44; 3; 6-2015; 415-4460925-9902CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1007/s10844-014-0339-yinfo:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007%2Fs10844-014-0339-yinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T14:39:19Zoai:ri.conicet.gov.ar:11336/50677instacron: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 14:39:19.859CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Semantic grounding of social annotations for enhancing resource classification in folksonomies
title Semantic grounding of social annotations for enhancing resource classification in folksonomies
spellingShingle Semantic grounding of social annotations for enhancing resource classification in folksonomies
Tommasel, Antonela
Folksonomies
Resource Classification
Semantic-Based Representations
Social Tagging Systems
title_short Semantic grounding of social annotations for enhancing resource classification in folksonomies
title_full Semantic grounding of social annotations for enhancing resource classification in folksonomies
title_fullStr Semantic grounding of social annotations for enhancing resource classification in folksonomies
title_full_unstemmed Semantic grounding of social annotations for enhancing resource classification in folksonomies
title_sort Semantic grounding of social annotations for enhancing resource classification in folksonomies
dc.creator.none.fl_str_mv Tommasel, Antonela
Godoy, Daniela Lis
author Tommasel, Antonela
author_facet Tommasel, Antonela
Godoy, Daniela Lis
author_role author
author2 Godoy, Daniela Lis
author2_role author
dc.subject.none.fl_str_mv Folksonomies
Resource Classification
Semantic-Based Representations
Social Tagging Systems
topic Folksonomies
Resource Classification
Semantic-Based Representations
Social Tagging 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 User-generated annotations in tagging or bookmarking sites such as Flickr or Delicious can provide a promising and interesting source of information for aiding tasks such as Web resource classification. However, the use of tags brings up some challenges. Since there are no constraints on the terms that can be used for tagging, noise and ambiguity are introduced when users annotate resources. Moreover, traditional bag-of-words representations ignore connections between terms and, thus, are affected by synonymity and hyponymia. Althougth tag-based representations are a valuable source for classifying resources, the problems associated with the unsupervised nature of tags may hinder classification results. This paper presents an approach for semantically analysing social annotations in order to attain enriched concept-based representations of Web resources. Representations are enriched with concepts extracted from WordNet and Wikipedia to overcome problems caused by natural language as well as enhancing the quality of information available for performing an effective classification of resources. Several strategies for tag pre-processing, concept disambiguation and incorporation of semantic entities to representations are discussed and evaluated in this paper. Experimental results showed that the strategies proposed to associate tags with conceptual entities allow improving resource classification results, outperforming traditional approaches based on bag-of-words representations.
Fil: Tommasel, Antonela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Fil: Godoy, Daniela Lis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
description User-generated annotations in tagging or bookmarking sites such as Flickr or Delicious can provide a promising and interesting source of information for aiding tasks such as Web resource classification. However, the use of tags brings up some challenges. Since there are no constraints on the terms that can be used for tagging, noise and ambiguity are introduced when users annotate resources. Moreover, traditional bag-of-words representations ignore connections between terms and, thus, are affected by synonymity and hyponymia. Althougth tag-based representations are a valuable source for classifying resources, the problems associated with the unsupervised nature of tags may hinder classification results. This paper presents an approach for semantically analysing social annotations in order to attain enriched concept-based representations of Web resources. Representations are enriched with concepts extracted from WordNet and Wikipedia to overcome problems caused by natural language as well as enhancing the quality of information available for performing an effective classification of resources. Several strategies for tag pre-processing, concept disambiguation and incorporation of semantic entities to representations are discussed and evaluated in this paper. Experimental results showed that the strategies proposed to associate tags with conceptual entities allow improving resource classification results, outperforming traditional approaches based on bag-of-words representations.
publishDate 2015
dc.date.none.fl_str_mv 2015-06
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/11336/50677
Tommasel, Antonela; Godoy, Daniela Lis; Semantic grounding of social annotations for enhancing resource classification in folksonomies; Springer; Journal Of Intelligent Information Systems; 44; 3; 6-2015; 415-446
0925-9902
CONICET Digital
CONICET
url http://hdl.handle.net/11336/50677
identifier_str_mv Tommasel, Antonela; Godoy, Daniela Lis; Semantic grounding of social annotations for enhancing resource classification in folksonomies; Springer; Journal Of Intelligent Information Systems; 44; 3; 6-2015; 415-446
0925-9902
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1007/s10844-014-0339-y
info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007%2Fs10844-014-0339-y
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 Springer
publisher.none.fl_str_mv Springer
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
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score 13.22299

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