Repository logo
 

Publication:
Comparative study of algorithms for mining association rules: Traditional approach versus multi-relational approach

dc.contributor.authorValêncio, Carlos Roberto [UNESP]
dc.contributor.authorOyama, Fernando Takeshi [UNESP]
dc.contributor.authorNeto, Paulo Scarpelini [UNESP]
dc.contributor.authorDe Souza, Rogéria Cristiane Gratão [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-27T11:26:14Z
dc.date.available2014-05-27T11:26:14Z
dc.date.issued2011-12-01
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.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.format.extent275-280
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.doi10.1109/PDCAT.2011.29
dc.identifier.lattes4644812253875832
dc.identifier.lattes5914651754517864
dc.identifier.orcid0000-0002-9325-3159
dc.identifier.orcid0000-0002-7449-9022
dc.identifier.scopus2-s2.0-84856658965
dc.identifier.urihttp://hdl.handle.net/11449/72858
dc.language.isoeng
dc.relation.ispartofParallel and Distributed Computing, Applications and Technologies, PDCAT Proceedings
dc.rights.accessRightsAcesso aberto
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.typeTrabalho apresentado em evento
dcterms.licensehttp://www.ieee.org/publications_standards/publications/rights/rights_policies.html
dspace.entity.typePublication
unesp.author.lattes4644812253875832[1]
unesp.author.lattes5914651754517864[4]
unesp.author.orcid0000-0002-9325-3159[1]
unesp.author.orcid0000-0002-7449-9022[4]
unesp.campusUniversidade Estadual Paulista (UNESP), Instituto de Biociências Letras e Ciências Exatas, São José do Rio Pretopt
unesp.departmentCiências da Computação e Estatística - IBILCEpt

Files