%0 Journal Article
%T Online data stream mining of recent frequent itemsets based on sliding window model<br>窗口模式下在线数据流中频繁项集的挖掘*
%A LI Ke
%A REN Jia-dong
%A <br>李可
%A 任家东
%J 计算机应用研究
%D 2010
%I 
%X 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.
%K online data stream
%K frequent items
%K sliding window<br>在线数据流
%K 频繁项集
%K 滑动窗
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=559D8B126CD4025EF8DCB137BA89899E&yid=140ECF96957D60B2&vid=DB817633AA4F79B9&iid=94C357A881DFC066&sid=A22DD5EE0F220B37&eid=6B11F480D189254A&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=8