量化关联规则挖掘及算法

Algorithms for Mining Quantitative Association Rules

提出了一种新的量化关联规则挖掘算法QAR及其增量式更新算法IUQAR .算法以模糊集理论为基础 ,利用模糊概念表示量化属性属性间的关联关系 ,克服了传统的离散分区方法的不足 ,使得规则的表示自然、简明 ,有利于专家理解 .同时 ,给出的算法IUQAR ,有效地解决了规则的维护问题 .

A novel algorithm, QAR, for mining quantitative association rules and an incremental updating algorithm, IUQAR, are proposed. Based on fuzzy set theory, a set of fuzzy concepts, which are defined in quantitative attribute domains, are employed to represent the revealed regularities among quantitative attributes and the drowbacks caused by the traditional discrete interval method are overcome. Besides, the algorithm, IUQAR, effectively solves maintenance problem of the regularities.