%0 Journal Article
%T Document clustering based on concept lattice<br>基于概念格的文本聚类
%A LI Jiang-hua
%A YANG Shu-xin
%A LIU Li-feng
%A <br>李江华
%A 杨书新
%A 刘利峰
%J 计算机应用
%D 2008
%I 
%X It is still difficult to deal with the dimension catastrophe, the sparse vector, and random selection of initial center in standard K-Means algorithm. A new clustering method based on concept lattice without evaluation function was proposed in this paper. Finally, an experiment was given. The results clearly show the outstanding performance of the proposed method in terms of correctness and efficiency.
%K K-Means<br>文本聚类
%K 评价函数
%K 概念格
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=BDE1C4E99390FC6836F34F1C2E0B826A&yid=67289AFF6305E306&vid=D3E34374A0D77D7F&iid=9CF7A0430CBB2DFD&sid=B74F270320BE8FD5&eid=48E05C7FFAD0392D&journal_id=1001-9081&journal_name=计算机应用&referenced_num=1&reference_num=8