Evaluating tag filtering techniques for web resource classification in folksonomies

Autores
Tourné, Nicolás; Godoy, Daniela Lis
Año de publicación
2012
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Social or collaborative tagging systems emerged as a novel classification scheme on the Web based on the collective knowledge of people. In sites such as Del.icio.us, Technorati or Flickr, users annotate a variety of resources, including Web pages, blogs, pictures, videos or bibliographic references; using freely chosen textual labels or tags. Underlying collaborative tagging systems are ternary data structures known as folksonomies relating resources and users through tags, this information facilitate accessing and browsing massive repositories of resources. Collective annotations provided by people in the form of tags can also be exploited to organize resources on-line in a more formal classification scheme such as the ones provided by hierarchies or directories, alleviating the task of manual classification commonly required by systems like directories on the Web. In this paper we present an empirical study carried out to determine the value of tags in resource classification. Furthermore, the use of several filtering and pre-processing operations to reduce the ambiguity and noise in tags are analyzed to determine whether they allow to increase the quality of resource classification.
Fil: Tourné, Nicolás. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas; 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
SOCIAL TAGGING SYSTEMS
WEB RESOURCE CLASSIFICATION
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/96795

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spelling Evaluating tag filtering techniques for web resource classification in folksonomiesTourné, NicolásGodoy, Daniela LisFOLKSONOMIESSOCIAL TAGGING SYSTEMSWEB RESOURCE CLASSIFICATIONhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Social or collaborative tagging systems emerged as a novel classification scheme on the Web based on the collective knowledge of people. In sites such as Del.icio.us, Technorati or Flickr, users annotate a variety of resources, including Web pages, blogs, pictures, videos or bibliographic references; using freely chosen textual labels or tags. Underlying collaborative tagging systems are ternary data structures known as folksonomies relating resources and users through tags, this information facilitate accessing and browsing massive repositories of resources. Collective annotations provided by people in the form of tags can also be exploited to organize resources on-line in a more formal classification scheme such as the ones provided by hierarchies or directories, alleviating the task of manual classification commonly required by systems like directories on the Web. In this paper we present an empirical study carried out to determine the value of tags in resource classification. Furthermore, the use of several filtering and pre-processing operations to reduce the ambiguity and noise in tags are analyzed to determine whether they allow to increase the quality of resource classification.Fil: Tourné, Nicolás. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas; 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; ArgentinaPergamon-Elsevier Science Ltd2012-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/96795Tourné, Nicolás; Godoy, Daniela Lis; Evaluating tag filtering techniques for web resource classification in folksonomies; Pergamon-Elsevier Science Ltd; Expert Systems with Applications; 39; 10; 8-2012; 9723-97290957-4174CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.eswa.2012.02.088info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0957417412003326info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:06:12Zoai:ri.conicet.gov.ar:11336/96795instacron: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:34982025-09-29 10:06:12.378CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Evaluating tag filtering techniques for web resource classification in folksonomies
title Evaluating tag filtering techniques for web resource classification in folksonomies
spellingShingle Evaluating tag filtering techniques for web resource classification in folksonomies
Tourné, Nicolás
FOLKSONOMIES
SOCIAL TAGGING SYSTEMS
WEB RESOURCE CLASSIFICATION
title_short Evaluating tag filtering techniques for web resource classification in folksonomies
title_full Evaluating tag filtering techniques for web resource classification in folksonomies
title_fullStr Evaluating tag filtering techniques for web resource classification in folksonomies
title_full_unstemmed Evaluating tag filtering techniques for web resource classification in folksonomies
title_sort Evaluating tag filtering techniques for web resource classification in folksonomies
dc.creator.none.fl_str_mv Tourné, Nicolás
Godoy, Daniela Lis
author Tourné, Nicolás
author_facet Tourné, Nicolás
Godoy, Daniela Lis
author_role author
author2 Godoy, Daniela Lis
author2_role author
dc.subject.none.fl_str_mv FOLKSONOMIES
SOCIAL TAGGING SYSTEMS
WEB RESOURCE CLASSIFICATION
topic FOLKSONOMIES
SOCIAL TAGGING SYSTEMS
WEB RESOURCE CLASSIFICATION
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Social or collaborative tagging systems emerged as a novel classification scheme on the Web based on the collective knowledge of people. In sites such as Del.icio.us, Technorati or Flickr, users annotate a variety of resources, including Web pages, blogs, pictures, videos or bibliographic references; using freely chosen textual labels or tags. Underlying collaborative tagging systems are ternary data structures known as folksonomies relating resources and users through tags, this information facilitate accessing and browsing massive repositories of resources. Collective annotations provided by people in the form of tags can also be exploited to organize resources on-line in a more formal classification scheme such as the ones provided by hierarchies or directories, alleviating the task of manual classification commonly required by systems like directories on the Web. In this paper we present an empirical study carried out to determine the value of tags in resource classification. Furthermore, the use of several filtering and pre-processing operations to reduce the ambiguity and noise in tags are analyzed to determine whether they allow to increase the quality of resource classification.
Fil: Tourné, Nicolás. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas; 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 Social or collaborative tagging systems emerged as a novel classification scheme on the Web based on the collective knowledge of people. In sites such as Del.icio.us, Technorati or Flickr, users annotate a variety of resources, including Web pages, blogs, pictures, videos or bibliographic references; using freely chosen textual labels or tags. Underlying collaborative tagging systems are ternary data structures known as folksonomies relating resources and users through tags, this information facilitate accessing and browsing massive repositories of resources. Collective annotations provided by people in the form of tags can also be exploited to organize resources on-line in a more formal classification scheme such as the ones provided by hierarchies or directories, alleviating the task of manual classification commonly required by systems like directories on the Web. In this paper we present an empirical study carried out to determine the value of tags in resource classification. Furthermore, the use of several filtering and pre-processing operations to reduce the ambiguity and noise in tags are analyzed to determine whether they allow to increase the quality of resource classification.
publishDate 2012
dc.date.none.fl_str_mv 2012-08
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/11336/96795
Tourné, Nicolás; Godoy, Daniela Lis; Evaluating tag filtering techniques for web resource classification in folksonomies; Pergamon-Elsevier Science Ltd; Expert Systems with Applications; 39; 10; 8-2012; 9723-9729
0957-4174
CONICET Digital
CONICET
url http://hdl.handle.net/11336/96795
identifier_str_mv Tourné, Nicolás; Godoy, Daniela Lis; Evaluating tag filtering techniques for web resource classification in folksonomies; Pergamon-Elsevier Science Ltd; Expert Systems with Applications; 39; 10; 8-2012; 9723-9729
0957-4174
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.eswa.2012.02.088
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0957417412003326
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Pergamon-Elsevier Science Ltd
publisher.none.fl_str_mv Pergamon-Elsevier Science Ltd
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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