%0 Journal Article
%T Application of Subtractive Clustering''s Fuzzy C-Means Categorization to Text Categorization<br>减聚类的模糊C-均值算法在文本分类中的应用
%A WANG Yue
%A CHAI Rui-Min
%A <br>王月
%A 柴瑞敏
%J 计算机系统应用
%D 2010
%I 
%X In this paper, fuzzy C-means categorization optimized by Subtractive clustering is applied to text clustering. First of all, the paper chooses a suitable text collection and deals with word segmentation of the text. Then, it extracts the internal idiocratic words of the documents, and uses word frequency statistics for the text dimensionality reduction processing, to choose the best eigenvector. Finally, after quantifying the text of the non-numerical data, it clusters the collections of text with fuzzy C-means algorithm which is optimized by Subtractive clustering, so as to enhance the effectiveness of text clustering.
%K fuzy clustering
%K text categorization
%K feature selection
%K VAM
%K subtractive clustering<br>模糊聚类
%K 文本分类
%K 特征选取
%K VSM
%K 减聚类
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D4F6864C950C88FFCE5B6C948A639E39&aid=D278892AEE4ADBD1EDDFC1E5ED455D3C&yid=140ECF96957D60B2&vid=2A8D03AD8076A2E3&iid=38B194292C032A66&sid=73579BC9CFB2D787&eid=0584DB487B4581F4&journal_id=1003-3254&journal_name=计算机系统应用&referenced_num=0&reference_num=5