摘要
本文提出了一种新的基于模糊集的关联规则挖掘算法,算法引入了模糊集理论和语义关联规则的概念,对数据库的数值属性进行了合理的非精确语义转换,然后通过改进剪枝部分被扫描项集的大小来提高算法的效率,避免了被扫描的集合长度按照指数型增长的趋势。
A kind of new AR mining algorithm based on fuzzy sets is presented in the paper.In this algorithm we introduce the fuzzy theory and the concept of semantics AR,carry through the inaccurate semantics conversion to the number property of database soundly,then improve the efficiency of algorithm by improving on the prune part being scanning by itemsets'size,it avoids the increasing current according to exponential of the set length being scanning.
出处
《微计算机信息》
北大核心
2008年第3期262-263,141,共3页
Control & Automation
关键词
数据挖掘
模糊集
关联规则
Data Mining
Fuzzy Set
Association Rules
