【摘要】 本文提出一种新的搜索最大频繁项集的算法。该算法使用多层扩展深度优先搜索方法,结合有效的前瞻剪枝策略,明显加速了最大频繁项集的生成,从而显著地降低了CPU时间。更多还原

【Abstract】 We present KMAX, a new depth-first search algorithm for mining maximal frequent itemsets. KMAX uses a novel technique called multilevel extension to extend the items in the search tree with an efficient look-ahead pruning method to prune the search space. Experimental comparison with the previous work indicates that it obviously accelerates the generation of maximal frequent itemsets ,therefore the CPU time is reduced remarkably.更多还原