基于OLAP的多维关联规则算法的研究

The Research and Application For Multidimensional Association Rules Algorithm Based on OLAP

多维关联规则是数据挖掘中的一个重要研究方向。本文针对Apriori算法与FP-Growth算法在数据立方体上应用的优缺点,提出了一种基于Apriori-Growth的多维关联规则算法,该方案将Apriori算法与FP树结构有机地结合起来,其优势在于不需要频繁地扫描数据立方体和产生频繁模式树,在一定程度上提高了算法效率。

Multidimensional data mining association rules is an important research direction. Based on the advantages and disadvantages of application for Apriori algorithm and FP-Growth algorithm in the data cube.In this paper,we propose an efficient algorithm for mining multidimensial association rules based on Apriori-Growth,which combine Apriori algorithm and FP-tree structure organically.The advantages of algorithm is that not need to scan data cubes frequently,which improved the efficiency of the algoritm to a certain extent.