Classification Rules to identify Context and Preference Information from Tourist’s Reviews

Autores
Aciar, Silvana Vanesa
Año de publicación
2010
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
In many tourist sites have been incorporate box to allow people interchange experience, written comments and valuation about products or services. Many of the tourists planning decision are based on third-party opinions. Text mining is the discipline that extracts information from written text by users/consumers in natural language to be understood by a computer system. In this paper is presented a text mining process to obtain classification rules in order to identify context information and consumer’s preferences from a review. User’s preferences are different according with a situation or context in which the review was expressed. This approach was exemplified by a case study using reviews from www.tripadvisor.com.
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
Contextual Information
Mining opinion
Text Mining
Classification tools
Tourism reviews
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/152655
Acceder
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network_name_str SEDICI (UNLP)
spelling Classification Rules to identify Context and Preference Information from Tourist’s ReviewsAciar, Silvana VanesaCiencias InformáticasContextual InformationMining opinionText MiningClassification toolsTourism reviewsIn many tourist sites have been incorporate box to allow people interchange experience, written comments and valuation about products or services. Many of the tourists planning decision are based on third-party opinions. Text mining is the discipline that extracts information from written text by users/consumers in natural language to be understood by a computer system. In this paper is presented a text mining process to obtain classification rules in order to identify context information and consumer’s preferences from a review. User’s preferences are different according with a situation or context in which the review was expressed. This approach was exemplified by a case study using reviews from www.tripadvisor.com.Sociedad Argentina de Informática e Investigación Operativa2010info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf138-149http://sedici.unlp.edu.ar/handle/10915/152655enginfo:eu-repo/semantics/altIdentifier/url/http://39jaiio.sadio.org.ar/sites/default/files/39jaiio-asai-13.pdfinfo:eu-repo/semantics/altIdentifier/issn/1850-2784info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-03T11:11:24Zoai:sedici.unlp.edu.ar:10915/152655Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 11:11:24.337SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Classification Rules to identify Context and Preference Information from Tourist’s Reviews
title Classification Rules to identify Context and Preference Information from Tourist’s Reviews
spellingShingle Classification Rules to identify Context and Preference Information from Tourist’s Reviews
Aciar, Silvana Vanesa
Ciencias Informáticas
Contextual Information
Mining opinion
Text Mining
Classification tools
Tourism reviews
title_short Classification Rules to identify Context and Preference Information from Tourist’s Reviews
title_full Classification Rules to identify Context and Preference Information from Tourist’s Reviews
title_fullStr Classification Rules to identify Context and Preference Information from Tourist’s Reviews
title_full_unstemmed Classification Rules to identify Context and Preference Information from Tourist’s Reviews
title_sort Classification Rules to identify Context and Preference Information from Tourist’s Reviews
dc.creator.none.fl_str_mv Aciar, Silvana Vanesa
author Aciar, Silvana Vanesa
author_facet Aciar, Silvana Vanesa
author_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
Contextual Information
Mining opinion
Text Mining
Classification tools
Tourism reviews
topic Ciencias Informáticas
Contextual Information
Mining opinion
Text Mining
Classification tools
Tourism reviews
dc.description.none.fl_txt_mv In many tourist sites have been incorporate box to allow people interchange experience, written comments and valuation about products or services. Many of the tourists planning decision are based on third-party opinions. Text mining is the discipline that extracts information from written text by users/consumers in natural language to be understood by a computer system. In this paper is presented a text mining process to obtain classification rules in order to identify context information and consumer’s preferences from a review. User’s preferences are different according with a situation or context in which the review was expressed. This approach was exemplified by a case study using reviews from www.tripadvisor.com.
Sociedad Argentina de Informática e Investigación Operativa
description In many tourist sites have been incorporate box to allow people interchange experience, written comments and valuation about products or services. Many of the tourists planning decision are based on third-party opinions. Text mining is the discipline that extracts information from written text by users/consumers in natural language to be understood by a computer system. In this paper is presented a text mining process to obtain classification rules in order to identify context information and consumer’s preferences from a review. User’s preferences are different according with a situation or context in which the review was expressed. This approach was exemplified by a case study using reviews from www.tripadvisor.com.
publishDate 2010
dc.date.none.fl_str_mv 2010
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
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status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/152655
url http://sedici.unlp.edu.ar/handle/10915/152655
dc.language.none.fl_str_mv eng
language eng
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info:eu-repo/semantics/altIdentifier/issn/1850-2784
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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