Mining negative rules: a literature review focusing on performance

Detalhes bibliográficos
Autor(a) principal: Colombo, Alexandre [UNESP]
Data de Publicação: 2021
Outros Autores: Spolon, Roberta [UNESP], Lobato, Renata Spolon [UNESP], Manacero Junior, Aleardo [UNESP], Cavenaghi, Marcos Antonio, Rocha, A., Goncalves, R., Penalvo, F. G., Martins, J.
Tipo de documento: Artigo de conferência
Idioma: por
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://hdl.handle.net/11449/237784
Resumo: Mining of frequent patterns and association rules is a Data Mining task that aims to determine consistent relationships among elements in a transaction database. Algorithms that consider the absence of elements perform the generation of so-called negative rules which result in associations of great interest for some applications, enabling it to obtain extra knowledge in comparison to the positive case. This type of association presents a problem regarding the increased amount of generated rules which demands adequate computational resources. This study presents a systematic review with the aim of grouping the concepts of the main contemporary works on this topic, in order to assist the development of future works in this subject.
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spelling Mining negative rules: a literature review focusing on performanceData miningFrequent patternsNegative association rulesParallel algorithmsSystematic literature reviewMining of frequent patterns and association rules is a Data Mining task that aims to determine consistent relationships among elements in a transaction database. Algorithms that consider the absence of elements perform the generation of so-called negative rules which result in associations of great interest for some applications, enabling it to obtain extra knowledge in comparison to the positive case. This type of association presents a problem regarding the increased amount of generated rules which demands adequate computational resources. This study presents a systematic review with the aim of grouping the concepts of the main contemporary works on this topic, in order to assist the development of future works in this subject.Univ Estadual Paulista, Dept Comp, Bauru, SP, BrazilUniv Estadual Paulista, Dept Ciencias Comp & Estat, Sao Jose Do Rio Preto, SP, BrazilHumber Inst Technol & Adv Learning, Fac Business, Toronto, ON, CanadaUniv Estadual Paulista, Dept Comp, Bauru, SP, BrazilUniv Estadual Paulista, Dept Ciencias Comp & Estat, Sao Jose Do Rio Preto, SP, BrazilIeeeUniversidade Estadual Paulista (UNESP)Humber Inst Technol & Adv LearningColombo, Alexandre [UNESP]Spolon, Roberta [UNESP]Lobato, Renata Spolon [UNESP]Manacero Junior, Aleardo [UNESP]Cavenaghi, Marcos AntonioRocha, A.Goncalves, R.Penalvo, F. G.Martins, J.2022-11-30T13:44:54Z2022-11-30T13:44:54Z2021-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject6Proceedings Of 2021 16th Iberian Conference On Information Systems And Technologies (cisti'2021). New York: Ieee, 6 p., 2021.2166-0727http://hdl.handle.net/11449/237784WOS:000824588500284Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPporProceedings Of 2021 16th Iberian Conference On Information Systems And Technologies (cisti'2021)info:eu-repo/semantics/openAccess2024-04-23T16:11:33Zoai:repositorio.unesp.br:11449/237784Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-04-23T16:11:33Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Mining negative rules: a literature review focusing on performance
title Mining negative rules: a literature review focusing on performance
spellingShingle Mining negative rules: a literature review focusing on performance
Colombo, Alexandre [UNESP]
Data mining
Frequent patterns
Negative association rules
Parallel algorithms
Systematic literature review
title_short Mining negative rules: a literature review focusing on performance
title_full Mining negative rules: a literature review focusing on performance
title_fullStr Mining negative rules: a literature review focusing on performance
title_full_unstemmed Mining negative rules: a literature review focusing on performance
title_sort Mining negative rules: a literature review focusing on performance
author Colombo, Alexandre [UNESP]
author_facet Colombo, Alexandre [UNESP]
Spolon, Roberta [UNESP]
Lobato, Renata Spolon [UNESP]
Manacero Junior, Aleardo [UNESP]
Cavenaghi, Marcos Antonio
Rocha, A.
Goncalves, R.
Penalvo, F. G.
Martins, J.
author_role author
author2 Spolon, Roberta [UNESP]
Lobato, Renata Spolon [UNESP]
Manacero Junior, Aleardo [UNESP]
Cavenaghi, Marcos Antonio
Rocha, A.
Goncalves, R.
Penalvo, F. G.
Martins, J.
author2_role author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (UNESP)
Humber Inst Technol & Adv Learning
dc.contributor.author.fl_str_mv Colombo, Alexandre [UNESP]
Spolon, Roberta [UNESP]
Lobato, Renata Spolon [UNESP]
Manacero Junior, Aleardo [UNESP]
Cavenaghi, Marcos Antonio
Rocha, A.
Goncalves, R.
Penalvo, F. G.
Martins, J.
dc.subject.por.fl_str_mv Data mining
Frequent patterns
Negative association rules
Parallel algorithms
Systematic literature review
topic Data mining
Frequent patterns
Negative association rules
Parallel algorithms
Systematic literature review
description Mining of frequent patterns and association rules is a Data Mining task that aims to determine consistent relationships among elements in a transaction database. Algorithms that consider the absence of elements perform the generation of so-called negative rules which result in associations of great interest for some applications, enabling it to obtain extra knowledge in comparison to the positive case. This type of association presents a problem regarding the increased amount of generated rules which demands adequate computational resources. This study presents a systematic review with the aim of grouping the concepts of the main contemporary works on this topic, in order to assist the development of future works in this subject.
publishDate 2021
dc.date.none.fl_str_mv 2021-01-01
2022-11-30T13:44:54Z
2022-11-30T13:44:54Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv Proceedings Of 2021 16th Iberian Conference On Information Systems And Technologies (cisti'2021). New York: Ieee, 6 p., 2021.
2166-0727
http://hdl.handle.net/11449/237784
WOS:000824588500284
identifier_str_mv Proceedings Of 2021 16th Iberian Conference On Information Systems And Technologies (cisti'2021). New York: Ieee, 6 p., 2021.
2166-0727
WOS:000824588500284
url http://hdl.handle.net/11449/237784
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv Proceedings Of 2021 16th Iberian Conference On Information Systems And Technologies (cisti'2021)
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 6
dc.publisher.none.fl_str_mv Ieee
publisher.none.fl_str_mv Ieee
dc.source.none.fl_str_mv Web of Science
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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