%0 Journal Article
%T Balanced Space-time Frequent Itemsets Mining over Data Stream<br>均衡时空挖掘数据流中频繁项集
%A SONG Kui-yong
%A REN Yong-gong
%A KOU Xiang-xia
%A <br>宋奎勇
%A 任永功
%A 寇香霞
%J 计算机科学
%D 2011
%I 
%X Data stream has characteristics of the flow, continuity, and the unbalanced distribution of item Minging frequent itemsets over data stream is a significant and challenging work. Presented a balanced space-time algorithm for mining frequent itemsets over data stream-Bala_Tree. The algorithm can only scan data stream once, make rapid cluster updates, periodical tree reconstruction and mine frequent itemsets based on classical algorithm. Experiments show that the algorithm can quickly scan and update data, realize the rational use of memory, accurate access to frectuent itemsets. Bala_ Tree algorithm is superior to other algorithms.
%K Data stream
%K Frequent itemsets
%K Balance
%K Bala_ Tree<br>数据流，频繁项集，均衡，Bala_Tree
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=17DDCED190714E79CFC0519510C9E90D&yid=9377ED8094509821&vid=16D8618C6164A3ED&iid=59906B3B2830C2C5&sid=3E0812ED84A7B31D&eid=6235172E4DDBA109&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=0