一种适用于中小数据集的关联规则挖掘算法

A Data Mining Algorithm of Association Rules Can Be Applied to Medium or Small Datasets

探讨了Apriori算法的改进问题,提出了一种适用于中小数据集的关联规则挖掘算法。该算法主要特点是简单、清晰、高效。一方面充分使用了内存的高效存贮,另一方面使用了位运算快速进行计数,同时简化了Apriori算法中频繁项集的计算,大大的减少了中间变量及其存贮的时间和空间,提高了关联规则挖掘的速度和效率。

This paper studies an improved algorithm of Apriori, then a new algorithm of association rules mining that can be applied to medium or small datasets is presented. The main characteristics of the algorithm are simple, clear, efficient. Firstly, the new algorithm takes good use of the efficient storing of memory, on the other hand it uses bit operation to take count fast. At the same time the algorithm simplifies the calculation of frequent itemsets of Apriori algorithm, consumedly reduces the temporary variables and its time and space of storage, improves the speed and efficiency of association rule data mining.