摘要
关联规则的提取是数据挖掘中的重要研究内容,对关联规则提取中的Apriori算法进行了分析与研究,针对该算法的运算效率不高,对该算法进行了优化。Partition算法以经典的Apriori算法为基础,通过将数据库分成几个互不相交的块来实现算法效率的提高。同时,还介绍了一种基于Apriori-Partition算法的可视化挖掘模型,并讨论了该可视化模型的实现方法。
Mining association rules are an important topic in the data mining field. The Apriori algorithm in mining association rules is studied and an improved effective algorithm is presented. The Partition algorithm is based on classical Apriori algorithm. Through divides into the database the block which several do not intersect mutually to realize the algorithm efficiency enhancement. Meantime a visualizing data-mining model is introduced based on Apriori-Partition algorithm, and the implementation method of visual model is discussed.
出处
《微计算机信息》
2009年第21期190-191,232,共3页
Control & Automation
