量化关联规则的几种开采算法及其比较

Algorithms of Discovering Quantitative Association Rules and Their Comparison

关联规则的发现是数据挖掘的一个重要方面 ,而数量关联规则的发现不同于传统的布尔型关联规则。属性值的离散映射是挖掘定量关联规则的一个重要环节 ,离散映射中属性值区间的划分粒度是影响数据挖掘质量的一个重要因素。该文介绍几种发现大型事务数据库中数量关联规则的算法 ,并对他们加以比较。

Discovering association rules is an important data mining problem. While discovering Quantitative Association Rules differs from traditional Boolean Association Rules. Mapping attribute's value into discrete characters is a key step in mining quantitative association rules,in which the partition granularity of attribute's value is a key factor affecting the quality of the result of data mining. In this paper, we' ll introduce some algorithms for discovering quantitative association rules between items in a large database of transactions,and compare them.