基于Apriori算法的多维关联规则挖掘研究

Research Multi-dimensional Association Rule Mining Based on Apriori Algorithm

关联规则是数据挖掘中的一个重要研究方向。经典的Apriori算法是一种最有影响的挖掘布尔型关联规则频繁项集的算法,但其并不适合挖掘近年来兴起的多维数据模型。在改进Apriori算法的基础上,提出了一种"二次剪枝"的算法,此算法适用于挖掘多维关联规则,并且在一定程度上提高了算法效率。

Association rules mining is very important in the application of data mining.Classic Apriori algorithm is one of the most influential association rules in mining boolean frequent itemsets algorithms,but is not suitable for mining multi-dimensional data model which rise in recent years.A ＂second cut＂ method is proposed,which is on the basis of the Apriori algorithm.The algorithm applies to multi-dimensional mining association rules,and to some extent improved the efficiency of the algorithm.