基于FP-Tree的最大频繁项目集综合更新算法

An Integrated Updating Algorithm for Mining Maximal Frequent Itemsets Based on FP-Tree

挖掘最大频繁项目集是多种数据挖掘应用中的关键问题,其挖掘过程的高花费要求对高效更新算法进行深入研究。为此,我们在改进频繁模式树(FP-Tree)的基础上提出了处理最小支持度和数据库都发生变化时的最大频繁项目集更新算法FUMFIA(Fast Updating Maximal Frequent Itemsets Algorithm)。通过对实验结果的分析可以看出,该算法在进行更新挖掘时具有很好的时空效率。

Mining maximal frequent itemsets is an important problem in many applications of data mining. And the great speeding in the process requires people to studyhighly efficient updationg algorithms. So we put forward a novel algorithm FUMFIA（fast updating maximal frequent itemsets algorithm） based on an improved frequent pattern tree to dealing with the problem of updating mining maximal frequent itemsets when both minimum support and database are changed. We can see clearly from experiment results that the algorithm has excellent performance in speeding time and using memory.