Exploring the data using Extended Association Rule Network
Autor(a) principal: | |
---|---|
Data de Publicação: | 2018 |
Outros Autores: | , , , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1109/BRACIS.2018.00064 http://hdl.handle.net/11449/186619 |
Resumo: | In this paper, we presented the Extended Association Rule Network (ExARN) to structure, prune and analyze a set of association rules, aiming to build hypothesis candidates. The ExARN extends the ARN, proposed by [2], allowing a more complete exploration. We validate the ExARN using two databases: contact lenses and hayes-roth, both available online for download. The results were validated by comparing the ExARN to the conventional ARN and also by comparing the results with a decision tree algorithms. The approach presented promising results, showing its capability to explain a set of objective items, aiding the user on the hypothesis building. |
id |
UNSP_d2e9e14bc91ca1d77dd75e1bbe1fce68 |
---|---|
oai_identifier_str |
oai:repositorio.unesp.br:11449/186619 |
network_acronym_str |
UNSP |
network_name_str |
Repositório Institucional da UNESP |
repository_id_str |
2946 |
spelling |
Exploring the data using Extended Association Rule NetworkAssociation RulesAssociation Rules NetworkHypothesis buildingData Analysis and Market Basket AnalysisIn this paper, we presented the Extended Association Rule Network (ExARN) to structure, prune and analyze a set of association rules, aiming to build hypothesis candidates. The ExARN extends the ARN, proposed by [2], allowing a more complete exploration. We validate the ExARN using two databases: contact lenses and hayes-roth, both available online for download. The results were validated by comparing the ExARN to the conventional ARN and also by comparing the results with a decision tree algorithms. The approach presented promising results, showing its capability to explain a set of objective items, aiding the user on the hypothesis building.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Univ Sao Paulo, Inst Ciencias Matemat & Comp, Sao Carlos, SP, BrazilItau Unibanco, Data Sci Team, Sao Paulo, BrazilUniv Estadual Paulista, Inst Geociencias & Ciencias Exatas, Rio Claro, BrazilUniv Estadual Paulista, Inst Geociencias & Ciencias Exatas, Rio Claro, BrazilFAPESP: 2016/17078-0IeeeUniversidade de São Paulo (USP)Itau UnibancoUniversidade Estadual Paulista (Unesp)Padua, Renan deCalcada, Dario BritoCarvalho, Veronica Oliveira de [UNESP]Rezende, Solange OliveiraIEEE2019-10-05T12:39:50Z2019-10-05T12:39:50Z2018-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject330-335http://dx.doi.org/10.1109/BRACIS.2018.000642018 7th Brazilian Conference On Intelligent Systems (bracis). New York: Ieee, p. 330-335, 2018.http://hdl.handle.net/11449/18661910.1109/BRACIS.2018.00064WOS:000457627300056Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2018 7th Brazilian Conference On Intelligent Systems (bracis)info:eu-repo/semantics/openAccess2021-10-22T21:10:00Zoai:repositorio.unesp.br:11449/186619Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462021-10-22T21:10Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Exploring the data using Extended Association Rule Network |
title |
Exploring the data using Extended Association Rule Network |
spellingShingle |
Exploring the data using Extended Association Rule Network Padua, Renan de Association Rules Association Rules Network Hypothesis building Data Analysis and Market Basket Analysis |
title_short |
Exploring the data using Extended Association Rule Network |
title_full |
Exploring the data using Extended Association Rule Network |
title_fullStr |
Exploring the data using Extended Association Rule Network |
title_full_unstemmed |
Exploring the data using Extended Association Rule Network |
title_sort |
Exploring the data using Extended Association Rule Network |
author |
Padua, Renan de |
author_facet |
Padua, Renan de Calcada, Dario Brito Carvalho, Veronica Oliveira de [UNESP] Rezende, Solange Oliveira IEEE |
author_role |
author |
author2 |
Calcada, Dario Brito Carvalho, Veronica Oliveira de [UNESP] Rezende, Solange Oliveira IEEE |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Universidade de São Paulo (USP) Itau Unibanco Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Padua, Renan de Calcada, Dario Brito Carvalho, Veronica Oliveira de [UNESP] Rezende, Solange Oliveira IEEE |
dc.subject.por.fl_str_mv |
Association Rules Association Rules Network Hypothesis building Data Analysis and Market Basket Analysis |
topic |
Association Rules Association Rules Network Hypothesis building Data Analysis and Market Basket Analysis |
description |
In this paper, we presented the Extended Association Rule Network (ExARN) to structure, prune and analyze a set of association rules, aiming to build hypothesis candidates. The ExARN extends the ARN, proposed by [2], allowing a more complete exploration. We validate the ExARN using two databases: contact lenses and hayes-roth, both available online for download. The results were validated by comparing the ExARN to the conventional ARN and also by comparing the results with a decision tree algorithms. The approach presented promising results, showing its capability to explain a set of objective items, aiding the user on the hypothesis building. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-01-01 2019-10-05T12:39:50Z 2019-10-05T12:39:50Z |
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 |
http://dx.doi.org/10.1109/BRACIS.2018.00064 2018 7th Brazilian Conference On Intelligent Systems (bracis). New York: Ieee, p. 330-335, 2018. http://hdl.handle.net/11449/186619 10.1109/BRACIS.2018.00064 WOS:000457627300056 |
url |
http://dx.doi.org/10.1109/BRACIS.2018.00064 http://hdl.handle.net/11449/186619 |
identifier_str_mv |
2018 7th Brazilian Conference On Intelligent Systems (bracis). New York: Ieee, p. 330-335, 2018. 10.1109/BRACIS.2018.00064 WOS:000457627300056 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2018 7th Brazilian Conference On Intelligent Systems (bracis) |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
330-335 |
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 |
|
_version_ |
1803046927467544576 |