Research on association rules mining algorithm with item constraints

被引：0

作者：

Lu, N ^{[1
]}

Wang-Zhe ^{[1
]}

Zhou, CG ^{[1
]}

Zhou, JZ ^{[1
]}

机构：

[1] Shenzhen Univ, Coll Informat Engn, Shenzhen, Peoples R China

来源：

2005 International Conference on Cyberworlds, Proceedings | 2005年

关键词：

data mining; association rules; item constrains; frequent item-set; lattice theory;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The issues in the field of association rules mining with specific items are discussed first. To solve the problems in the ordinary algorithm, we put forward a new but efficient mining algorithm with item-constraints, called EclatII. We then give an analysis on the performance of the algorithm as well as on its strategy. The experimental result shows that the Eclatll algorithm is more robust in items of using "low support" and "long pattern" association rules than others.

引用

页码：325 / 329

页数：5

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