Contrast set mining in temporal databases
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/1822/33862 |
Resumo: | Understanding the underlying differences between groups or classes in certain contexts can be of the utmost importance. Contrast set mining relies on discovering significant patterns by contrasting two or more groups. A contrast set is a conjunction of attribute–value pairs that differ meaningfully in its distribution across groups. A previously proposed technique is rules for contrast sets, which seeks to express each contrast set found in terms of rules. This work extends rules for contrast sets to a temporal data mining task. We define a set of temporal patterns in order to capture the significant changes in the contrasts discovered along the considered time line. To evaluate the proposal accuracy and ability to discover relevant information, two different real-life data sets were studied using this approach. |
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Contrast set mining in temporal databasesSoftware engineeringArtificial intelligenceKnowledge acquisitionKnowledge representationKnowledge base systemknowledge base < systemknowledge base < systemScience & TechnologyUnderstanding the underlying differences between groups or classes in certain contexts can be of the utmost importance. Contrast set mining relies on discovering significant patterns by contrasting two or more groups. A contrast set is a conjunction of attribute–value pairs that differ meaningfully in its distribution across groups. A previously proposed technique is rules for contrast sets, which seeks to express each contrast set found in terms of rules. This work extends rules for contrast sets to a temporal data mining task. We define a set of temporal patterns in order to capture the significant changes in the contrasts discovered along the considered time line. To evaluate the proposal accuracy and ability to discover relevant information, two different real-life data sets were studied using this approach.(undefined)WileyElsevierUniversidade do MinhoMagalhães, AndréAzevedo, Paulo J.20152015-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/33862engMagalhaes, A., & Azevedo, P. J. (2015). Contrast set mining in temporal databases. Expert Systems, 32(3), 435-443. doi: 10.1111/exsy.120801468-039410.1111/exsy.12080info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T12:23:27Zoai:repositorium.sdum.uminho.pt:1822/33862Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:17:10.183734Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Contrast set mining in temporal databases |
title |
Contrast set mining in temporal databases |
spellingShingle |
Contrast set mining in temporal databases Magalhães, André Software engineering Artificial intelligence Knowledge acquisition Knowledge representation Knowledge base system knowledge base < system knowledge base < system Science & Technology |
title_short |
Contrast set mining in temporal databases |
title_full |
Contrast set mining in temporal databases |
title_fullStr |
Contrast set mining in temporal databases |
title_full_unstemmed |
Contrast set mining in temporal databases |
title_sort |
Contrast set mining in temporal databases |
author |
Magalhães, André |
author_facet |
Magalhães, André Azevedo, Paulo J. |
author_role |
author |
author2 |
Azevedo, Paulo J. |
author2_role |
author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Magalhães, André Azevedo, Paulo J. |
dc.subject.por.fl_str_mv |
Software engineering Artificial intelligence Knowledge acquisition Knowledge representation Knowledge base system knowledge base < system knowledge base < system Science & Technology |
topic |
Software engineering Artificial intelligence Knowledge acquisition Knowledge representation Knowledge base system knowledge base < system knowledge base < system Science & Technology |
description |
Understanding the underlying differences between groups or classes in certain contexts can be of the utmost importance. Contrast set mining relies on discovering significant patterns by contrasting two or more groups. A contrast set is a conjunction of attribute–value pairs that differ meaningfully in its distribution across groups. A previously proposed technique is rules for contrast sets, which seeks to express each contrast set found in terms of rules. This work extends rules for contrast sets to a temporal data mining task. We define a set of temporal patterns in order to capture the significant changes in the contrasts discovered along the considered time line. To evaluate the proposal accuracy and ability to discover relevant information, two different real-life data sets were studied using this approach. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015 2015-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/1822/33862 |
url |
http://hdl.handle.net/1822/33862 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Magalhaes, A., & Azevedo, P. J. (2015). Contrast set mining in temporal databases. Expert Systems, 32(3), 435-443. doi: 10.1111/exsy.12080 1468-0394 10.1111/exsy.12080 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Wiley Elsevier |
publisher.none.fl_str_mv |
Wiley Elsevier |
dc.source.none.fl_str_mv |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799132622848262144 |