MR-Radix: a multi-relational data mining algorithm

dc.contributorUniversidade Estadual Paulista (UNESP)
dc.creatorValencio, Carlos R.
dc.creatorOyama, Fernando T.
dc.creatorScarpelini, Paulo
dc.creatorColombini, Angelo C.
dc.creatorSouza, Rogeria C. G. de |Correa, Pedro L. P.
dc.creatorCansian, Adriano Mauro
dc.date2015-04-27T11:56:08Z
dc.date2016-10-25T20:47:17Z
dc.date2015-04-27T11:56:08Z
dc.date2016-10-25T20:47:17Z
dc.date2012
dc.date.accessioned2017-04-06T08:11:16Z
dc.date.available2017-04-06T08:11:16Z
dc.identifierHuman-centric Computing and Information Sciences, v. 2, 2012.
dc.identifier2192-1962
dc.identifierhttp://hdl.handle.net/11449/122906
dc.identifierhttp://acervodigital.unesp.br/handle/11449/122906
dc.identifierhttp://dx.doi.org/10.1186/2192-1962-2-4
dc.identifier0095921943345974
dc.identifier5564862621270143
dc.identifier5914651754517864
dc.identifier3640608958277159
dc.identifierhttp://dx.doi.org/10.1186/2192-1962-2-4
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/933523
dc.descriptionBackground: Once multi-relational approach has emerged as an alternative for analyzing structured data such as relational databases, since they allow applying data mining in multiple tables directly, thus avoiding expensive joining operations and semantic losses, this work proposes an algorithm with multi-relational approach. Methods: Aiming to compare traditional approach performance and multi-relational for mining association rules, this paper discusses an empirical study between PatriciaMine - an traditional algorithm - and its corresponding multi-relational proposed, MR-Radix. Results: This work showed advantages of the multi-relational approach in performance over several tables, which avoids the high cost for joining operations from multiple tables and semantic losses. The performance provided by the algorithm MR-Radix shows faster than PatriciaMine, despite handling complex multi-relational patterns. The utilized memory indicates a more conservative growth curve for MR-Radix than PatriciaMine, which shows the increase in demand of frequent items in MR-Radix does not result in a significant growth of utilized memory like in PatriciaMine. Conclusion: The comparative study between PatriciaMine and MR-Radix confirmed efficacy of the multi-relational approach in data mining process both in terms of execution time and in relation to memory usage. Besides that, the multi-relational proposed algorithm, unlike other algorithms of this approach, is efficient for use in large relational databases.
dc.languageeng
dc.relationHuman-centric Computing and Information Sciences
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectMR-Radix
dc.subjectMulti-relational data mining
dc.subjectAssociation rules
dc.subjectMining frequent itemsets
dc.subjectRelational databases
dc.titleMR-Radix: a multi-relational data mining algorithm
dc.typeOtro


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