%0 Journal Article
%T Text clustering based on genetic fuzzy C-means algorithm<br>基于遗传FCM算法的文本聚类
%A KUANG Hang
%A LUO Jun
%A <br>况夯
%A 罗军
%J 计算机应用
%D 2009
%I 
%X A text clustering method based on genetic fuzzy c-means algorithm was proposed. At first, latent semantic index was used to reduce the dimension of text feature and then the number of text class was obtained through analyzing the validity of clustering. At last, genetic FCM algorithm was used to cluster the text. The proposed method overcomes the flaw of FCM algorithm which may converge to local optimum, and it resolves the problem of FCM algorithm which is sensitive to the initialized value of cluster center. The experimental results show that the proposed method has better clustering effect.
%K Text clustering
%K feature selection
%K latent semantic index (LSI)
%K Genetic Algorithm (GA)
%K Fuzzy C-means clustering<br>文本聚类
%K 特征选择
%K 潜在语义索引
%K 遗传算法
%K 模糊C均值聚类
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=4870B68F286BD4DBC0A863E4423F1680&yid=DE12191FBD62783C&vid=771469D9D58C34FF&iid=0B39A22176CE99FB&sid=C7A2B92569DF5458&eid=A3F93694B058F76C&journal_id=1001-9081&journal_name=计算机应用&referenced_num=1&reference_num=8