AWSC: An approach to Web service classification based on machine learning techniques

Autores
Crasso, Marco Patricio; Zunino Suarez, Alejandro Octavio; Campo, Marcelo Ricardo
Año de publicación
2008
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
A Web service is a Web accessible software that can be published, located and invoked by using standard Web protocols. Automatically determining the category of a Web service, from several pre-defined categories, is an important problem with many applications such as service discovery, semantic annotation and service matching. This paper describes AWSC (Automatic Web Service Classification), an automatic classifier of Web service descriptions. AWSC exploits the connections between the category of a Web service and the information commonly found in standard descriptions. In addition, AWSC bridges different styles for describing services by combining text mining and machine learning techniques. Experimental evaluations show that this combination helps our classification system at improving its precision. In addition, we report an experimental comparison of AWSC with a related work.
Fil: Crasso, Marco Patricio. 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: Zunino Suarez, Alejandro Octavio. 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: Campo, Marcelo Ricardo. 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
Web services
Text classification
Machine learning
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:11336/244807
Acceder
id CONICETDig_fc7cfcbcd0101f64828b596508606b37
oai_identifier_str oai:ri.conicet.gov.ar:11336/244807
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling AWSC: An approach to Web service classification based on machine learning techniquesCrasso, Marco PatricioZunino Suarez, Alejandro OctavioCampo, Marcelo RicardoWeb servicesText classificationMachine learninghttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1A Web service is a Web accessible software that can be published, located and invoked by using standard Web protocols. Automatically determining the category of a Web service, from several pre-defined categories, is an important problem with many applications such as service discovery, semantic annotation and service matching. This paper describes AWSC (Automatic Web Service Classification), an automatic classifier of Web service descriptions. AWSC exploits the connections between the category of a Web service and the information commonly found in standard descriptions. In addition, AWSC bridges different styles for describing services by combining text mining and machine learning techniques. Experimental evaluations show that this combination helps our classification system at improving its precision. In addition, we report an experimental comparison of AWSC with a related work.Fil: Crasso, Marco Patricio. 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: Zunino Suarez, Alejandro Octavio. 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: Campo, Marcelo Ricardo. 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; ArgentinaSociedad Iberoamericana de Inteligencia Artificial2008-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/244807Crasso, Marco Patricio; Zunino Suarez, Alejandro Octavio; Campo, Marcelo Ricardo; AWSC: An approach to Web service classification based on machine learning techniques; Sociedad Iberoamericana de Inteligencia Artificial; Inteligencia Artificial; 12; 37; 6-2008; 25-361988-3064CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://journal.iberamia.org/public/Vol.1-14.html#2008info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:43:09Zoai:ri.conicet.gov.ar:11336/244807instacron: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 10:43:09.637CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv AWSC: An approach to Web service classification based on machine learning techniques
title AWSC: An approach to Web service classification based on machine learning techniques
spellingShingle AWSC: An approach to Web service classification based on machine learning techniques
Crasso, Marco Patricio
Web services
Text classification
Machine learning
title_short AWSC: An approach to Web service classification based on machine learning techniques
title_full AWSC: An approach to Web service classification based on machine learning techniques
title_fullStr AWSC: An approach to Web service classification based on machine learning techniques
title_full_unstemmed AWSC: An approach to Web service classification based on machine learning techniques
title_sort AWSC: An approach to Web service classification based on machine learning techniques
dc.creator.none.fl_str_mv Crasso, Marco Patricio
Zunino Suarez, Alejandro Octavio
Campo, Marcelo Ricardo
author Crasso, Marco Patricio
author_facet Crasso, Marco Patricio
Zunino Suarez, Alejandro Octavio
Campo, Marcelo Ricardo
author_role author
author2 Zunino Suarez, Alejandro Octavio
Campo, Marcelo Ricardo
author2_role author
author
dc.subject.none.fl_str_mv Web services
Text classification
Machine learning
topic Web services
Text classification
Machine learning
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv A Web service is a Web accessible software that can be published, located and invoked by using standard Web protocols. Automatically determining the category of a Web service, from several pre-defined categories, is an important problem with many applications such as service discovery, semantic annotation and service matching. This paper describes AWSC (Automatic Web Service Classification), an automatic classifier of Web service descriptions. AWSC exploits the connections between the category of a Web service and the information commonly found in standard descriptions. In addition, AWSC bridges different styles for describing services by combining text mining and machine learning techniques. Experimental evaluations show that this combination helps our classification system at improving its precision. In addition, we report an experimental comparison of AWSC with a related work.
Fil: Crasso, Marco Patricio. 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: Zunino Suarez, Alejandro Octavio. 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: Campo, Marcelo Ricardo. 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 A Web service is a Web accessible software that can be published, located and invoked by using standard Web protocols. Automatically determining the category of a Web service, from several pre-defined categories, is an important problem with many applications such as service discovery, semantic annotation and service matching. This paper describes AWSC (Automatic Web Service Classification), an automatic classifier of Web service descriptions. AWSC exploits the connections between the category of a Web service and the information commonly found in standard descriptions. In addition, AWSC bridges different styles for describing services by combining text mining and machine learning techniques. Experimental evaluations show that this combination helps our classification system at improving its precision. In addition, we report an experimental comparison of AWSC with a related work.
publishDate 2008
dc.date.none.fl_str_mv 2008-06
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/11336/244807
Crasso, Marco Patricio; Zunino Suarez, Alejandro Octavio; Campo, Marcelo Ricardo; AWSC: An approach to Web service classification based on machine learning techniques; Sociedad Iberoamericana de Inteligencia Artificial; Inteligencia Artificial; 12; 37; 6-2008; 25-36
1988-3064
CONICET Digital
CONICET
url http://hdl.handle.net/11336/244807
identifier_str_mv Crasso, Marco Patricio; Zunino Suarez, Alejandro Octavio; Campo, Marcelo Ricardo; AWSC: An approach to Web service classification based on machine learning techniques; Sociedad Iberoamericana de Inteligencia Artificial; Inteligencia Artificial; 12; 37; 6-2008; 25-36
1988-3064
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://journal.iberamia.org/public/Vol.1-14.html#2008
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
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Sociedad Iberoamericana de Inteligencia Artificial
publisher.none.fl_str_mv Sociedad Iberoamericana de Inteligencia Artificial
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_ 1844614465744535552
score 13.069144

Publicaciones similares