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FTRA 2012

Abstract

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.

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.

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.

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.

Details

Title
MR-Radix: a multi-relational data mining algorithm
Author
Valêncio, Carlos Roberto; Oyama, Fernando Takeshi; Scarpelini Neto, Paulo; Colombini, Angelo Cesar; Cansian, Adriano Mauro; de Souza, Rogéria Cristiane; Gratão; Corrêa, Pedro Luiz; Pizzigatti
Pages
1-17
Publication year
2012
Publication date
Mar 2012
Publisher
Korea Information Processing Society, Computer Software Research Group
e-ISSN
21921962
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
1652935690
Copyright
FTRA 2012