%0 Journal Article
%T R-means: Exploiting Association Rules as Means for Text Clustering<br>R-means：以关联规则为簇中心的文本聚类
%A LONG Hao
%A FENG Jian-Lin
%A LI Qu
%A <br>龙昊
%A 冯剑琳
%A 李曲
%J 计算机科学
%D 2005
%I 
%X This paper proposes a new text clustering algorithm called R-means which integrates k-means with associa- tion rule (or frequent itemset). R-means exploits association rules as means of clusters and refines clusters by an itera- tive procedure which is similar to that of k-means. R-means not only inherits the simplicity of k-means, but also gener- ates more comprehensive cluster labels which are described by association rules. The experiments with several real data sets have demonstrated that R-means can achieve quite well precision and high performance.
%K Association rules
%K Frequent itemset
%K Means of clusters
%K Associative text clustering<br>关联规则
%K 频繁项目集
%K 簇中心
%K 关联文本聚类
%K R-means算法
%K 信息检索
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=86A94AC3CFC9A44A&yid=2DD7160C83D0ACED&vid=9971A5E270697F23&iid=9CF7A0430CBB2DFD&sid=3F0AF5EDBC960DB0&eid=BA79719BCA7341D5&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=13