%0 Journal Article
%T Application of a non-linear dimension reduction algorithm on document clustering<br>非线性维数约减算法在文档聚类中的应用
%A SUN Yue-heng
%A HOU Yue-xian
%A HE Pi-lian
%A <br>孙越恒
%A 侯越先
%A 何丕廉
%J 计算机应用
%D 2008
%I 
%X This paper presented a non-linear dimension reduction algorithm-Self-organizing Isometric Embedding (SIE) to compress high-dimensional document data. The algorithm was then validated in document clustering by being compared with the typical linear dimension reduction algorithm-Latent Semantic Indexing (LSI). Experimental results show that while significantly lowering the complexity, the performance of SIE is better than that of LSI and the benchmark.
%K non-linear dimension reduction
%K linear dimension reduction
%K self-organizing isometric embedding
%K docunmet clustering<br>非线性维数约减
%K 线性维数约减
%K 自组织等距嵌入
%K 文档聚类
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=18DCE2EB66C03B16115BECE0F623F5A0&yid=67289AFF6305E306&vid=D3E34374A0D77D7F&iid=0B39A22176CE99FB&sid=8CE1095CD639AEF4&eid=D397660E39E3E461&journal_id=1001-9081&journal_name=计算机应用&referenced_num=0&reference_num=8