Comparative Study of Algorithms for Mining Association Rules: Traditional Approach versus Multi-relational Approach

C. R. Valêncio, Fernando Takeshi Oyama, Paulo Scarpelini Neto, Rogéria Cristiane Gratão de Souza
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引用次数: 4

Abstract

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 multi-relational advantage in performance over several tables, which avoids the costly join operations from multiple tables.
关联规则挖掘算法的比较研究:传统方法与多关系方法
多关系数据挖掘方法作为结构化数据(如关系数据库)分析的替代方法而出现。与传统算法不同,多关系提议允许直接挖掘多个表,避免了代价高昂的连接操作。本文对传统的Patricia Mine算法及其相应的多关系算法进行了比较研究,为了评价两种方法在关联规则挖掘中的性能,将MR-Radix算法应用于关系数据库。本研究提出了两个原创贡献:提出了一种多关系MR-Radix算法,该算法在关系数据库中使用效率很高,无论是在执行时间方面还是在内存使用方面;提出了经验方法,即多关系在多个表的性能上具有优势,避免了多个表的昂贵连接操作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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