%0 Journal Article
%T Survey on data stream classification technologies<br>数据流分类技术研究综述*
%A HUANG Shu-cheng
%A QU Ya-hui
%A <br>黄树成
%A 曲亚辉
%J 计算机应用研究
%D 2009
%I 
%X The high speed, continuous and virtual infinite, and time-changing inherent features of streaming data invalidate the traditional technologies of data analysis and data mining, or motivate the need for evolving themselves. This paper put emphasis on data stream classification, proposed a few critical issues accompanying with data stream classification, surveyed typical classification approaches. Furthermore,presented a new framework exploiting active learning and semi-supervised learning to attack the disadvantages of current technologies.
%K data stream mining
%K classification
%K active learning
%K semi-supervised learning<br>数据流挖掘
%K 分类
%K 主动学习
%K 半监督学习
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=338D0E3615CC8AF9043CED357F921022&yid=DE12191FBD62783C&vid=96C778EE049EE47D&iid=F3090AE9B60B7ED1&sid=C20678A0CB1486E0&eid=EE4409B89EE372C6&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=22