Abstract: Aiming at the problem of NewMoment algorithm frequently do leftcheck operation in the data mining process, which leads to the low efficiency of algorithm, this paper proposes an improved method called LevelMoment to improve the NewMoment algorithm which mines frequent closed itemsets over data streams. In this process, a new data structure that added in level node, called LevelCET, is proposed. On this structure, using level checking strategy and optimum frequent closed items checking strategy can quickly tap all the frequent closed itemsets over data streams. Experimental results show that the algorithm has good performance on run time and storage space.

Key words: data stream, frequent closed itemset, sliding window, level checking strategy, optimum frequent closed itemsets checking strategy

摘要： NewMoment算法在数据挖掘过程中频繁地进行左检测操作，导致算法运行效率低下。针对该问题，提出一种改进的数据流频繁闭项集挖掘算法——LevelMoment。在该算法中，给出一种新的加入层次节点的数据结构LevelCET，在此结构上通过层次检测策略与最佳频繁闭项集检测策略，快速地挖掘数据流滑动窗口中的所有频繁闭项集。实验结果表明，改进算法在运行时间与存储空间上性能较优。

关键词: 数据流, 频繁闭项集, 滑动窗口, 层次检测策略, 最佳频繁闭项集检测策略

CLC Number: 

• TP311