E-Mail Processing with Fuzzy SOMs and Association Rules

Autores
Lanzarini, Laura Cristina; Villa Monte, Augusto; Estrebou, César Armando
Año de publicación
2011
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
E-mail texts are hard to process due to their short length. In this article, the use of a diffuse neural network that is capable of identifying the most relevant terms in a set of e-mails is proposed. The associations between these terms will be measured through association rules built with the terms identified by the network. The metrics support, confidence and interest of the rules will be used to qualify the corresponding terms. The method proposed has been used to process e-mails of the PACENI Project (Support Project for Improving First-Year Teaching in Courses of Studies in Exact and Natural Sciences, Economic Science and Computer Science). With this type of analysis, the most common topics of student questions have been identified. Even though this new information can have various applications, they all involve, as a first instance, an improvement in student service.
Facultad de Informática
Materia
Ciencias Informáticas
Almacenamiento y Recuperación de la Información
Procesamiento Automatizado de Datos
Internet
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/9693
Acceder
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network_name_str SEDICI (UNLP)
spelling E-Mail Processing with Fuzzy SOMs and Association RulesLanzarini, Laura CristinaVilla Monte, AugustoEstrebou, César ArmandoCiencias InformáticasAlmacenamiento y Recuperación de la InformaciónProcesamiento Automatizado de DatosInternetE-mail texts are hard to process due to their short length. In this article, the use of a diffuse neural network that is capable of identifying the most relevant terms in a set of e-mails is proposed. The associations between these terms will be measured through association rules built with the terms identified by the network. The metrics support, confidence and interest of the rules will be used to qualify the corresponding terms. The method proposed has been used to process e-mails of the PACENI Project (Support Project for Improving First-Year Teaching in Courses of Studies in Exact and Natural Sciences, Economic Science and Computer Science). With this type of analysis, the most common topics of student questions have been identified. Even though this new information can have various applications, they all involve, as a first instance, an improvement in student service.Facultad de Informática2011info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf41-46http://sedici.unlp.edu.ar/handle/10915/9693enginfo:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Apr11-7.pdfinfo:eu-repo/semantics/altIdentifier/issn/1666-6038info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc/3.0/Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-22T16:32:22Zoai:sedici.unlp.edu.ar:10915/9693Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-22 16:32:22.469SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv E-Mail Processing with Fuzzy SOMs and Association Rules
title E-Mail Processing with Fuzzy SOMs and Association Rules
spellingShingle E-Mail Processing with Fuzzy SOMs and Association Rules
Lanzarini, Laura Cristina
Ciencias Informáticas
Almacenamiento y Recuperación de la Información
Procesamiento Automatizado de Datos
Internet
title_short E-Mail Processing with Fuzzy SOMs and Association Rules
title_full E-Mail Processing with Fuzzy SOMs and Association Rules
title_fullStr E-Mail Processing with Fuzzy SOMs and Association Rules
title_full_unstemmed E-Mail Processing with Fuzzy SOMs and Association Rules
title_sort E-Mail Processing with Fuzzy SOMs and Association Rules
dc.creator.none.fl_str_mv Lanzarini, Laura Cristina
Villa Monte, Augusto
Estrebou, César Armando
author Lanzarini, Laura Cristina
author_facet Lanzarini, Laura Cristina
Villa Monte, Augusto
Estrebou, César Armando
author_role author
author2 Villa Monte, Augusto
Estrebou, César Armando
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Almacenamiento y Recuperación de la Información
Procesamiento Automatizado de Datos
Internet
topic Ciencias Informáticas
Almacenamiento y Recuperación de la Información
Procesamiento Automatizado de Datos
Internet
dc.description.none.fl_txt_mv E-mail texts are hard to process due to their short length. In this article, the use of a diffuse neural network that is capable of identifying the most relevant terms in a set of e-mails is proposed. The associations between these terms will be measured through association rules built with the terms identified by the network. The metrics support, confidence and interest of the rules will be used to qualify the corresponding terms. The method proposed has been used to process e-mails of the PACENI Project (Support Project for Improving First-Year Teaching in Courses of Studies in Exact and Natural Sciences, Economic Science and Computer Science). With this type of analysis, the most common topics of student questions have been identified. Even though this new information can have various applications, they all involve, as a first instance, an improvement in student service.
Facultad de Informática
description E-mail texts are hard to process due to their short length. In this article, the use of a diffuse neural network that is capable of identifying the most relevant terms in a set of e-mails is proposed. The associations between these terms will be measured through association rules built with the terms identified by the network. The metrics support, confidence and interest of the rules will be used to qualify the corresponding terms. The method proposed has been used to process e-mails of the PACENI Project (Support Project for Improving First-Year Teaching in Courses of Studies in Exact and Natural Sciences, Economic Science and Computer Science). With this type of analysis, the most common topics of student questions have been identified. Even though this new information can have various applications, they all involve, as a first instance, an improvement in student service.
publishDate 2011
dc.date.none.fl_str_mv 2011
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
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://sedici.unlp.edu.ar/handle/10915/9693
url http://sedici.unlp.edu.ar/handle/10915/9693
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Apr11-7.pdf
info:eu-repo/semantics/altIdentifier/issn/1666-6038
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc/3.0/
Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc/3.0/
Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
dc.format.none.fl_str_mv application/pdf
41-46
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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