%0 Journal Article
%T Research of Text Clustering Based on Fuzzy Granular Computing<br>基于模糊粒度计算的K-means文本聚类算法研究
%A ZHANG Xia
%A WANG Su-zhen
%A YIN Yi-xin
%A ZHAO Hai-long
%A <br>张霞
%A 王素贞
%A 尹怡欣
%A 赵海龙
%J 计算机科学
%D 2010
%I 
%X The traditional K-means is very sensitive to initial clustering centers and the clustering result will wave with the different initial inpul To remove this sensitivity,a new method was proposed to get initial clustering centers.This method is as follows:provide a normalized distance function in the fuzzy granularity space of data objects,then use the function to do a initial clustering work to these data objects who has a less distance than granularity dλ,then get the initial clustering centers.The test shows this method has such advantages on increasing the rate of accuracy and reducing the program times.
%K Fuzzy
%K Granular computing
%K K-means
%K Text cluster
%K Normalized distance function<br>模糊
%K 粒度
%K K-means
%K 文本聚类
%K 归一化距离函数
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=AF2D0EE1D106843211981DB2DC9C7B01&yid=140ECF96957D60B2&vid=42425781F0B1C26E&iid=0B39A22176CE99FB&sid=79D2EF35F60110C2&eid=CC0ECB9C52F1B85F&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=5