Quality measures for fuzzy predicates in conjunctive and disjunctive normal forms
Association rule mining is a very popular data mining technique. Rules in this technique are often used to identify and represent de-pendencies between attributes in databases. Specifically, fuzzy association rules are rules that use the concepts of fuzzy sets and can be considered as a special case...
- Autores:
-
Ceruto Cordovés, Taymi
Lapeira Mena, Orenia
Rosete Suarez, Alejandro
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2014
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/52515
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/52515
http://bdigital.unal.edu.co/46860/
- Palabra clave:
- minería de datos
predicados difusos
medidas de calidad
forma normal conjuntiva
disyuntiva
data mining
fuzzy predicate
quality measures
conjunctive and disjunctive normal forms
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
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Quality measures for fuzzy predicates in conjunctive and disjunctive normal forms |
| title |
Quality measures for fuzzy predicates in conjunctive and disjunctive normal forms |
| spellingShingle |
Quality measures for fuzzy predicates in conjunctive and disjunctive normal forms minería de datos predicados difusos medidas de calidad forma normal conjuntiva disyuntiva data mining fuzzy predicate quality measures conjunctive and disjunctive normal forms |
| title_short |
Quality measures for fuzzy predicates in conjunctive and disjunctive normal forms |
| title_full |
Quality measures for fuzzy predicates in conjunctive and disjunctive normal forms |
| title_fullStr |
Quality measures for fuzzy predicates in conjunctive and disjunctive normal forms |
| title_full_unstemmed |
Quality measures for fuzzy predicates in conjunctive and disjunctive normal forms |
| title_sort |
Quality measures for fuzzy predicates in conjunctive and disjunctive normal forms |
| dc.creator.fl_str_mv |
Ceruto Cordovés, Taymi Lapeira Mena, Orenia Rosete Suarez, Alejandro |
| dc.contributor.author.spa.fl_str_mv |
Ceruto Cordovés, Taymi Lapeira Mena, Orenia Rosete Suarez, Alejandro |
| dc.subject.proposal.spa.fl_str_mv |
minería de datos predicados difusos medidas de calidad forma normal conjuntiva disyuntiva data mining fuzzy predicate quality measures conjunctive and disjunctive normal forms |
| topic |
minería de datos predicados difusos medidas de calidad forma normal conjuntiva disyuntiva data mining fuzzy predicate quality measures conjunctive and disjunctive normal forms |
| description |
Association rule mining is a very popular data mining technique. Rules in this technique are often used to identify and represent de-pendencies between attributes in databases. Specifically, fuzzy association rules are rules that use the concepts of fuzzy sets and can be considered as a special case of fuzzy predicates. Many quality measures have been defined for fuzzy association rules, but all consider a specific structure: antecedent and consequence. In the case of fuzzy predicates in the normal form (i.e., conjunctive or disjunctive), it is necessary to define different quality measures that do not consider the structure as an antecedent or a consequence. The only available measure for this scenario is the fuzzy predicate truth value (FPTV), which has serious limitations. The evaluation of fuzzy predicates in the normal form through appropriate quality measures has not yet been clearly defined in the literature. Thus, we propose several quality measures specifically for fuzzy predicates in the conjunctive (CNF) and disjunctive (DNF) normal forms. Experi-mental studies illustrate the use of the proposed measures and allow some general conclusions about each measure. |
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2014 |
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2014-11-21 |
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2019-06-29T14:35:56Z |
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2019-06-29T14:35:56Z |
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Artículo de revista |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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info:eu-repo/semantics/article |
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http://purl.org/coar/resource_type/c_6501 |
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https://repositorio.unal.edu.co/handle/unal/52515 |
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http://bdigital.unal.edu.co/46860/ |
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spa |
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spa |
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http://revistas.unal.edu.co/index.php/ingeinv/article/view/41638 |
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Universidad Nacional de Colombia Revistas electrónicas UN Ingeniería e Investigación Ingeniería e Investigación |
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Ingeniería e Investigación; Vol. 34, núm. 3 (2014); 63-69 Ingeniería e Investigación; Vol. 34, núm. 3 (2014); 63-69 2248-8723 0120-5609 |
| dc.relation.references.spa.fl_str_mv |
Ceruto Cordovés, Taymi and Lapeira Mena, Orenia and Rosete Suarez, Alejandro (2014) Quality measures for fuzzy predicates in conjunctive and disjunctive normal forms. Ingeniería e Investigación; Vol. 34, núm. 3 (2014); 63-69 Ingeniería e Investigación; Vol. 34, núm. 3 (2014); 63-69 2248-8723 0120-5609 . |
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Derechos reservados - Universidad Nacional de Colombia |
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http://purl.org/coar/access_right/c_abf2 |
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Atribución-NoComercial 4.0 Internacional |
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Atribución-NoComercial 4.0 InternacionalDerechos reservados - Universidad Nacional de Colombiahttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Ceruto Cordovés, Taymib07bb48e-6c7e-438c-a1e5-59b5eca3bc89300Lapeira Mena, Orenia233660ea-1a8f-44ed-becc-670bf5e108d4300Rosete Suarez, Alejandro993fa4f2-8e6e-4702-baf8-4942fd83fd513002019-06-29T14:35:56Z2019-06-29T14:35:56Z2014-11-21https://repositorio.unal.edu.co/handle/unal/52515http://bdigital.unal.edu.co/46860/Association rule mining is a very popular data mining technique. Rules in this technique are often used to identify and represent de-pendencies between attributes in databases. Specifically, fuzzy association rules are rules that use the concepts of fuzzy sets and can be considered as a special case of fuzzy predicates. Many quality measures have been defined for fuzzy association rules, but all consider a specific structure: antecedent and consequence. In the case of fuzzy predicates in the normal form (i.e., conjunctive or disjunctive), it is necessary to define different quality measures that do not consider the structure as an antecedent or a consequence. The only available measure for this scenario is the fuzzy predicate truth value (FPTV), which has serious limitations. The evaluation of fuzzy predicates in the normal form through appropriate quality measures has not yet been clearly defined in the literature. Thus, we propose several quality measures specifically for fuzzy predicates in the conjunctive (CNF) and disjunctive (DNF) normal forms. Experi-mental studies illustrate the use of the proposed measures and allow some general conclusions about each measure.La extracción de las reglas de asociación es una técnica de minería de datos muy popular, las cuales son utilizadas a menudo para identificar y representar dependencias entre atributos en bases de datos. Específicamente, las reglas de asociación difusas utilizan conceptos de conjuntos difusos y pueden ser vistas como un caso especial de predicados difusos. Muchas medidas de calidad han sido definidas para reglas de asociación difusa, pero todas consideran la estructura específica de reglas: antecedente y conse-cuente.En el caso general de predicados difusos en forma normal (conjuntiva o disyuntiva), es necesario definir diferentes medidas de cali-dad que no estén en función de antecedente y consecuente, puesto que la única medida disponible para ello, es el valor de verdad para predicados difusos (FPTV) y tiene serias limitaciones. La evaluación de un predicado difuso en forma normal, a través de medidas adecuadas de calidad no ha sido todavía claramente definida por otros autores. Por esa razón, en este trabajo se proponen varias medidas de calidad para los predicados difusos, en formas normal conjuntiva o disyuntiva. Los experimentos demuestran el uso que se le puede dar a las métricas propuestas y permiten llegar a conclusiones generales de cada una de ellas.application/pdfspaUniversidad Nacional de Colombia - Facultad de Ingenieríahttp://revistas.unal.edu.co/index.php/ingeinv/article/view/41638Universidad Nacional de Colombia Revistas electrónicas UN Ingeniería e InvestigaciónIngeniería e InvestigaciónIngeniería e Investigación; Vol. 34, núm. 3 (2014); 63-69 Ingeniería e Investigación; Vol. 34, núm. 3 (2014); 63-69 2248-8723 0120-5609Ceruto Cordovés, Taymi and Lapeira Mena, Orenia and Rosete Suarez, Alejandro (2014) Quality measures for fuzzy predicates in conjunctive and disjunctive normal forms. Ingeniería e Investigación; Vol. 34, núm. 3 (2014); 63-69 Ingeniería e Investigación; Vol. 34, núm. 3 (2014); 63-69 2248-8723 0120-5609 .Quality measures for fuzzy predicates in conjunctive and disjunctive normal formsArtículo de revistainfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Texthttp://purl.org/redcol/resource_type/ARTminería de datospredicados difusosmedidas de calidadforma normal conjuntivadisyuntivadata miningfuzzy predicatequality measuresconjunctive and disjunctive normal formsORIGINAL41638-231280-4-PB.pdfapplication/pdf240306https://repositorio.unal.edu.co/bitstream/unal/52515/1/41638-231280-4-PB.pdfc0bb817358b3df88233c1a5fd291bb8cMD5141638-189251-1-SP.pdfapplication/pdf168480https://repositorio.unal.edu.co/bitstream/unal/52515/2/41638-189251-1-SP.pdf1add0a6a73bd2da87cb68f81bd6aa0b4MD52THUMBNAIL41638-231280-4-PB.pdf.jpg41638-231280-4-PB.pdf.jpgGenerated Thumbnailimage/jpeg8616https://repositorio.unal.edu.co/bitstream/unal/52515/3/41638-231280-4-PB.pdf.jpg7f84944feafa72f801bdd36d19c03795MD5341638-189251-1-SP.pdf.jpg41638-189251-1-SP.pdf.jpgGenerated Thumbnailimage/jpeg7331https://repositorio.unal.edu.co/bitstream/unal/52515/4/41638-189251-1-SP.pdf.jpgff24a9ff1d58f25f09d7e79bb096388eMD54unal/52515oai:repositorio.unal.edu.co:unal/525152024-03-02 23:08:27.418Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.co |