MLFI:新的最大长度频繁项集挖掘方法

MLFI:New method for maximum length frequent itemsets mining

在理解现有的最大长度频繁项集挖掘问题的定义,探索最大长度频繁项集的几个具体应用后,提出了一种新的基于FP-tree(Frequent Pattern tree)结构的最大长度频繁项集挖掘方法——MLFI算法。该算法仅对初始的FP-tree实现遍历操作,从而完成对最大长度频繁项集的挖掘。在算法整个执行过程中,仅用到了一棵初始的FP-tree。理论分析和实验证明,该算法加快了挖掘速度,提高了挖掘效率。

After the current definition of the maximum length frequent itemsets mining problem is understood and its many practical applications are explored,an FP-tree-based algorithm is proposed for the mining problem.Maximum length frequent itemsets are mined while traversing the FP-tree in the algorithm.There is only an initial FP-tree.Theoretic analysis and experiments show that the algorithm accelerates the speed to traverse the tree and improves the mining efficiency.