摘要： 频繁闭合模式集可唯一确定频繁模式完全集。根据数据流的特点，提出一种挖掘频繁闭合项集的算法，该算法将数据流分段，用DSFCI_tree动态存储潜在频繁闭合项集，对每一批到来的数据流，建立局部DSFCI_tree，进而对全局DSFCI_tree进行更新并剪枝，从而有效地挖掘整个数据流中的频繁闭合模式。实验表明，该算法具有良好的时间和空间效率。

关键词: 数据挖掘, 数据流, 关联规则, 频繁闭合项集

Abstract: The set of frequent closed patterns uniquely determines the complete set of all frequent patterns. According to the features of data streams, a new algorithm is proposed for mining the frequent closed patterns. The data streams are partitioned into a set of segments, and a DSFCI_tree is used to store the potential frequent closed patterns dynamically. With the arrival of each batch of data, the algorithm builds a corresponding local DSFCI_tree, then updates and prunes the global DSFCI_tree effectively to mine the frequent closed patterns in the entire data streams. The experiments and analysis show that the algorithm has good performance.

Key words: data mining, data streams, association rule, frequent closed itemsets

中图分类号: 

• TP311