%0 Journal Article
%T An Algorithm for Clustering Evolving Text Data Stream with Outliers<br>一种新的演化文本流聚类算法
%A DENG Wei-Wei
%A PENG Hong
%A <br>邓维维
%A 彭宏
%J 计算机科学
%D 2007
%I 
%X As a branch of clustering, data stream clustering has become a hot spot in data mining. Although there are many stream clustering algorithms, they are only suitable for low dimensional numeric data type, and few of them are designed for high dimensional text streams. A novel online micro cluster structure based on the traditional stream clustering framework was proposed and it is suitable for clustering text. Dividing the online micro cluster into potential and outlier micro clusters also brings advantage when outliers appear frequently in stream. Experiments show that these methods bring advancements for processing text streams when compared to others.
%K Clustering
%K Data stream
%K Text stream<br>聚类
%K 数据流
%K 文本流
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=AC90537328779B17&yid=A732AF04DDA03BB3&vid=339D79302DF62549&iid=9CF7A0430CBB2DFD&sid=F122871CC7EC92DC&eid=B344543C2864D684&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=11