Online data stream mining of recent frequent itemsets based on sliding window model
窗口模式下在线数据流中频繁项集的挖掘*

This paper proposed a one-pass data stream mining algorithm to mine the recent frequent itemsets in data streams with a sliding window based on transactions.To reduce the cost of time and memory needed to slide the windows,denoted each items a bit-sequence representations. Basing on dealing with the representations,can find frequent patterns in data streams efficiently,and the sequent of frequent 2-items is correct.This paper named the method MRFI-SW(mining recent frequent itemsets by sliding window)algorithm.