Pattern discovery and model construction: an evolutionary learning and data mining approach

Autores
Zhou, Harry
Año de publicación
2006
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
In the information age, knowledge leads to profits, power and success. As an ancestor of data mining, machine learning has concerned itself with discovery of new knowledge on its own. This paper presents experiment results produced by genetic algorithms in the domains of model construction and event predictions, the areas where data mining systems have been focusing on. The experiment results have shown that genetic algorithms are able to discover useful patterns and regularities in large sets of data, and to construct models that conceptualize input data. It demonstrates that genetic algorithms are a powerful and useful learning algorithm for solving fundamental tasks data mining systems are facing today.
Applications in Artificial Intelligence - Knowledge Discovery
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Algorithms
Conocimiento
genetic algorithms
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/24215
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/24215
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Pattern discovery and model construction: an evolutionary learning and data mining approachZhou, HarryCiencias InformáticasAlgorithmsConocimientogenetic algorithmsIn the information age, knowledge leads to profits, power and success. As an ancestor of data mining, machine learning has concerned itself with discovery of new knowledge on its own. This paper presents experiment results produced by genetic algorithms in the domains of model construction and event predictions, the areas where data mining systems have been focusing on. The experiment results have shown that genetic algorithms are able to discover useful patterns and regularities in large sets of data, and to construct models that conceptualize input data. It demonstrates that genetic algorithms are a powerful and useful learning algorithm for solving fundamental tasks data mining systems are facing today.Applications in Artificial Intelligence - Knowledge DiscoveryRed de Universidades con Carreras en Informática (RedUNCI)2006-08info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/24215enginfo:eu-repo/semantics/altIdentifier/isbn/0-387-34655-4info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-11-12T10:20:39Zoai:sedici.unlp.edu.ar:10915/24215Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-11-12 10:20:39.386SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Pattern discovery and model construction: an evolutionary learning and data mining approach
title Pattern discovery and model construction: an evolutionary learning and data mining approach
spellingShingle Pattern discovery and model construction: an evolutionary learning and data mining approach
Zhou, Harry
Ciencias Informáticas
Algorithms
Conocimiento
genetic algorithms
title_short Pattern discovery and model construction: an evolutionary learning and data mining approach
title_full Pattern discovery and model construction: an evolutionary learning and data mining approach
title_fullStr Pattern discovery and model construction: an evolutionary learning and data mining approach
title_full_unstemmed Pattern discovery and model construction: an evolutionary learning and data mining approach
title_sort Pattern discovery and model construction: an evolutionary learning and data mining approach
dc.creator.none.fl_str_mv Zhou, Harry
author Zhou, Harry
author_facet Zhou, Harry
author_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
Algorithms
Conocimiento
genetic algorithms
topic Ciencias Informáticas
Algorithms
Conocimiento
genetic algorithms
dc.description.none.fl_txt_mv In the information age, knowledge leads to profits, power and success. As an ancestor of data mining, machine learning has concerned itself with discovery of new knowledge on its own. This paper presents experiment results produced by genetic algorithms in the domains of model construction and event predictions, the areas where data mining systems have been focusing on. The experiment results have shown that genetic algorithms are able to discover useful patterns and regularities in large sets of data, and to construct models that conceptualize input data. It demonstrates that genetic algorithms are a powerful and useful learning algorithm for solving fundamental tasks data mining systems are facing today.
Applications in Artificial Intelligence - Knowledge Discovery
Red de Universidades con Carreras en Informática (RedUNCI)
description In the information age, knowledge leads to profits, power and success. As an ancestor of data mining, machine learning has concerned itself with discovery of new knowledge on its own. This paper presents experiment results produced by genetic algorithms in the domains of model construction and event predictions, the areas where data mining systems have been focusing on. The experiment results have shown that genetic algorithms are able to discover useful patterns and regularities in large sets of data, and to construct models that conceptualize input data. It demonstrates that genetic algorithms are a powerful and useful learning algorithm for solving fundamental tasks data mining systems are facing today.
publishDate 2006
dc.date.none.fl_str_mv 2006-08
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
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info:ar-repo/semantics/documentoDeConferencia
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status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/24215
url http://sedici.unlp.edu.ar/handle/10915/24215
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/isbn/0-387-34655-4
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
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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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