基于多剪枝格的频繁项集表示与挖掘

Representation and mining of frequent itemsets based on multiple pruned concept lattices

文章在研究基于剪枝概念格的频繁项集表示的基础上,提出了基于多剪枝概念格模型的频繁项集表示与挖掘方法。该方法在多剪枝格基础上进行导出频繁项集的合并,进而获得全局频繁项集,有效地降低了频繁项集表示的规模;理论分析和实验结果表明,该方法能获得满足用户要求的近似所有全局频繁项集。

Based on the representation of frequent itemsets of the pruned concept lattice, the merging method of frequent, itemsets based on the multiple pruned concept lattice（MPCL） is proposed. The size of frequent itemsets is reduced effectively with the method. Theoretic analysis and experiment resuits show that the presented method is competent to extract almost all the global frequent itemsets, thus satisfying the users.