A Knowledge Representation Example of a Fuzzy Database Implemented in PostgreSQL, with FIRST-2 and FSQL

Autores
Urrutia, Angélica; Galindo, José; Sepúlveda, Alejandro
Año de publicación
2010
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
In this article we present how to implement fuzzy databases based on the relational model. This approach includes many fuzzy attribute types, which can express the most of fuzzy knowledge types. These fuzzy attribute types include imprecise attributes, fuzzy attributes associated with one or more attributes, or with an independent meaning. In order to represent such fuzzy information we must study two aspects of fuzzy information: how to represent fuzzy data and how to represent fuzzy metaknowledge data. This second information is very important and it must be considered in any fuzzy database. This article studies the fuzzy metaknowledge data for any fuzzy attribute and how to represent both in a relational database. Finally, we apply all of this in a real example in the context of medical appointments.
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
Fuzzy relational databases
Fuzzy attributes
Fuzzy degrees
Fuzzy metaknowledge
Representation of Fuzzy Knowledge
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:10915/152581
Acceder
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network_name_str SEDICI (UNLP)
spelling A Knowledge Representation Example of a Fuzzy Database Implemented in PostgreSQL, with FIRST-2 and FSQLUrrutia, AngélicaGalindo, JoséSepúlveda, AlejandroCiencias InformáticasFuzzy relational databasesFuzzy attributesFuzzy degreesFuzzy metaknowledgeRepresentation of Fuzzy KnowledgeIn this article we present how to implement fuzzy databases based on the relational model. This approach includes many fuzzy attribute types, which can express the most of fuzzy knowledge types. These fuzzy attribute types include imprecise attributes, fuzzy attributes associated with one or more attributes, or with an independent meaning. In order to represent such fuzzy information we must study two aspects of fuzzy information: how to represent fuzzy data and how to represent fuzzy metaknowledge data. This second information is very important and it must be considered in any fuzzy database. This article studies the fuzzy metaknowledge data for any fuzzy attribute and how to represent both in a relational database. Finally, we apply all of this in a real example in the context of medical appointments.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/pdf37-47http://sedici.unlp.edu.ar/handle/10915/152581enginfo:eu-repo/semantics/altIdentifier/url/http://39jaiio.sadio.org.ar/sites/default/files/39jaiio-asai-04.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:UNLP2025-10-15T11:31:09Zoai:sedici.unlp.edu.ar:10915/152581Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-15 11:31:09.402SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv A Knowledge Representation Example of a Fuzzy Database Implemented in PostgreSQL, with FIRST-2 and FSQL
title A Knowledge Representation Example of a Fuzzy Database Implemented in PostgreSQL, with FIRST-2 and FSQL
spellingShingle A Knowledge Representation Example of a Fuzzy Database Implemented in PostgreSQL, with FIRST-2 and FSQL
Urrutia, Angélica
Ciencias Informáticas
Fuzzy relational databases
Fuzzy attributes
Fuzzy degrees
Fuzzy metaknowledge
Representation of Fuzzy Knowledge
title_short A Knowledge Representation Example of a Fuzzy Database Implemented in PostgreSQL, with FIRST-2 and FSQL
title_full A Knowledge Representation Example of a Fuzzy Database Implemented in PostgreSQL, with FIRST-2 and FSQL
title_fullStr A Knowledge Representation Example of a Fuzzy Database Implemented in PostgreSQL, with FIRST-2 and FSQL
title_full_unstemmed A Knowledge Representation Example of a Fuzzy Database Implemented in PostgreSQL, with FIRST-2 and FSQL
title_sort A Knowledge Representation Example of a Fuzzy Database Implemented in PostgreSQL, with FIRST-2 and FSQL
dc.creator.none.fl_str_mv Urrutia, Angélica
Galindo, José
Sepúlveda, Alejandro
author Urrutia, Angélica
author_facet Urrutia, Angélica
Galindo, José
Sepúlveda, Alejandro
author_role author
author2 Galindo, José
Sepúlveda, Alejandro
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Fuzzy relational databases
Fuzzy attributes
Fuzzy degrees
Fuzzy metaknowledge
Representation of Fuzzy Knowledge
topic Ciencias Informáticas
Fuzzy relational databases
Fuzzy attributes
Fuzzy degrees
Fuzzy metaknowledge
Representation of Fuzzy Knowledge
dc.description.none.fl_txt_mv In this article we present how to implement fuzzy databases based on the relational model. This approach includes many fuzzy attribute types, which can express the most of fuzzy knowledge types. These fuzzy attribute types include imprecise attributes, fuzzy attributes associated with one or more attributes, or with an independent meaning. In order to represent such fuzzy information we must study two aspects of fuzzy information: how to represent fuzzy data and how to represent fuzzy metaknowledge data. This second information is very important and it must be considered in any fuzzy database. This article studies the fuzzy metaknowledge data for any fuzzy attribute and how to represent both in a relational database. Finally, we apply all of this in a real example in the context of medical appointments.
Sociedad Argentina de Informática e Investigación Operativa
description In this article we present how to implement fuzzy databases based on the relational model. This approach includes many fuzzy attribute types, which can express the most of fuzzy knowledge types. These fuzzy attribute types include imprecise attributes, fuzzy attributes associated with one or more attributes, or with an independent meaning. In order to represent such fuzzy information we must study two aspects of fuzzy information: how to represent fuzzy data and how to represent fuzzy metaknowledge data. This second information is very important and it must be considered in any fuzzy database. This article studies the fuzzy metaknowledge data for any fuzzy attribute and how to represent both in a relational database. Finally, we apply all of this in a real example in the context of medical appointments.
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
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/152581
url http://sedici.unlp.edu.ar/handle/10915/152581
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://39jaiio.sadio.org.ar/sites/default/files/39jaiio-asai-04.pdf
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
37-47
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
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instname_str Universidad Nacional de La Plata
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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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