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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/72858
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dc.contributor.authorValêncio, Carlos Roberto-
dc.contributor.authorOyama, Fernando Takeshi-
dc.contributor.authorNeto, Paulo Scarpelini-
dc.contributor.authorDe Souza, Rogéria Cristiane Gratão-
dc.date.accessioned2014-05-27T11:26:14Z-
dc.date.accessioned2016-10-25T18:35:52Z-
dc.date.available2014-05-27T11:26:14Z-
dc.date.available2016-10-25T18:35:52Z-
dc.date.issued2011-12-01-
dc.identifierhttp://dx.doi.org/10.1109/PDCAT.2011.29-
dc.identifier.citationParallel and Distributed Computing, Applications and Technologies, PDCAT Proceedings, p. 275-280.-
dc.identifier.urihttp://hdl.handle.net/11449/72858-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/72858-
dc.description.abstractThe multi-relational Data Mining approach has emerged as alternative to the analysis of structured data, such as relational databases. Unlike traditional algorithms, the multi-relational proposals allow mining directly multiple tables, avoiding the costly join operations. In this paper, is presented a comparative study involving the traditional Patricia Mine algorithm and its corresponding multi-relational proposed, MR-Radix in order to evaluate the performance of two approaches for mining association rules are used for relational databases. This study presents two original contributions: the proposition of an algorithm multi-relational MR-Radix, which is efficient for use in relational databases, both in terms of execution time and in relation to memory usage and the presentation of the empirical approach multirelational advantage in performance over several tables, which avoids the costly join operations from multiple tables. © 2011 IEEE.en
dc.format.extent275-280-
dc.language.isoeng-
dc.sourceScopus-
dc.subjectAssociation rules-
dc.subjectMining frequent itemsets-
dc.subjectMR-radix-
dc.subjectMulti-relational data mining-
dc.subjectRelational databases-
dc.subjectComparative studies-
dc.subjectEmpirical approach-
dc.subjectExecution time-
dc.subjectJoin operation-
dc.subjectMemory usage-
dc.subjectMining associations-
dc.subjectMultirelational data mining-
dc.subjectRelational Database-
dc.subjectStructured data-
dc.subjectData mining-
dc.subjectDatabase systems-
dc.subjectAlgorithms-
dc.titleComparative study of algorithms for mining association rules: Traditional approach versus multi-relational approachen
dc.typeoutro-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.description.affiliationDepto. de Ciências de Computação e Estatística Universidade Estadual Paulista - Unesp, São José do Rio Preto-
dc.description.affiliationUnespDepto. de Ciências de Computação e Estatística Universidade Estadual Paulista - Unesp, São José do Rio Preto-
dc.identifier.doi10.1109/PDCAT.2011.29-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofParallel and Distributed Computing, Applications and Technologies, PDCAT Proceedings-
dc.identifier.scopus2-s2.0-84856658965-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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