TBAR:: An efficient method for association rule mining in relational databases

被引：64

作者：

Berzal, F ^{[1
]}

Cubero, JC ^{[1
]}

Marín, N ^{[1
]}

Serrano, JM ^{[1
]}

机构：

[1] Univ Granada, Dept Ciencias Comp & Intelligencia Artifical, Granada 18071, Spain

来源：

DATA & KNOWLEDGE ENGINEERING | 2001年 / 37卷 / 01期

关键词：

data mining; association rules; relational databases;

D O I：

10.1016/S0169-023X(00)00055-0

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we propose a new algorithm for efficient association rule mining, which we apply in order to discover interesting patterns in relational databases. Our algorithm, which is called Tree-Based Association Rule mining (TBAR), redefines the notion of item and employs an effective tree data structure. It can also use techniques such as Direct Hashing and Pruning (DHP). Experiments with real-life datasets show that TEAR outperforms Apriori, a well-known and widely used algorithm. (C) 2001 Elsevier Science B.V. All rights reserved.

引用

页码：47 / 64

页数：18

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