POST-PROCESSING ASSOCIATION RULES WITH CLUSTERING AND OBJECTIVE MEASURES

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (Unesp)-
Autor(es): dc.contributorUniversidade de São Paulo (USP)-
Autor(es): dc.creatorCarvalho, Veronica Oliveira de [UNESP]-
Autor(es): dc.creatorSantos, Fabiano Fernandes dos-
Autor(es): dc.creatorRezende, Solange Oliveira-
Autor(es): dc.creatorZhang, R.-
Autor(es): dc.creatorCordeiro, J.-
Autor(es): dc.creatorLi, X-
Autor(es): dc.creatorZhang, Z.-
Autor(es): dc.creatorZhang, J.-
Data de aceite: dc.date.accessioned2022-02-22T00:12:43Z-
Data de disponibilização: dc.date.available2022-02-22T00:12:43Z-
Data de envio: dc.date.issued2020-12-09-
Data de envio: dc.date.issued2020-12-09-
Data de envio: dc.date.issued2011-01-01-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/197458-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/197458-
Descrição: dc.descriptionThe post-processing of association rules is a difficult task, since a large number of patterns can be obtained. Many approaches have been developed to overcome this problem, as objective measures and clustering, which are respectively used to: (i) highlight the potentially interesting knowledge in domain; (ii) structure the domain, organizing the rules in groups that contain, somehow, similar knowledge. However, objective measures don't reduce nor organize the collection of rules, making the understanding of the domain difficult. On the other hand, clustering doesn't reduce the exploration space nor direct the user to find interesting knowledge, making the search for relevant knowledge not so easy. This work proposes the PAR-COM (Post-processing Association Rules with Clustering and Objective Measures) methodology that, combining clustering and objective measures, reduces the association rule exploration space directing the user to what is potentially interesting. Thereby, PAR-COM minimises the user's effort during the post-processing process.-
Descrição: dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)-
Descrição: dc.descriptionUniv Estadual Paulista, Inst Geociencias & Ciencias Exatas, Rio Claro, Brazil-
Descrição: dc.descriptionUniv Sao Paulo, Inst Ciencias Matemat & Comp, Sao Carlos, SP, Brazil-
Descrição: dc.descriptionUniv Estadual Paulista, Inst Geociencias & Ciencias Exatas, Rio Claro, Brazil-
Descrição: dc.descriptionFAPESP: 2010/07879-0-
Formato: dc.format54-63-
Idioma: dc.languageen-
Publicador: dc.publisherInsticc-inst Syst Technologies Information Control & Communication-
Relação: dc.relationIceis 2011: Proceedings Of The 13th International Conference On Enterprise Information Systems, Vol 1-
???dc.source???: dc.sourceWeb of Science-
Palavras-chave: dc.subjectAssociation rules-
Palavras-chave: dc.subjectPost-processing-
Palavras-chave: dc.subjectClustering and objective measures-
Título: dc.titlePOST-PROCESSING ASSOCIATION RULES WITH CLUSTERING AND OBJECTIVE MEASURES-
Aparece nas coleções:Repositório Institucional - Unesp

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