Comparative study of algorithms for mining association rules: Traditional approach versus multi-relational approach
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Data
2011-12-01
Autores
Valêncio, Carlos Roberto [UNESP]
Oyama, Fernando Takeshi [UNESP]
Neto, Paulo Scarpelini [UNESP]
De Souza, Rogéria Cristiane Gratão [UNESP]
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Resumo
The 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.
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Palavras-chave
Association rules, Mining frequent itemsets, MR-radix, Multi-relational data mining, Relational databases, Comparative studies, Empirical approach, Execution time, Join operation, Memory usage, Mining associations, Multirelational data mining, Relational Database, Structured data, Data mining, Database systems, Algorithms
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Parallel and Distributed Computing, Applications and Technologies, PDCAT Proceedings, p. 275-280.