%0 Journal Article
%T Network Search Based on Weighted Vector Space Model<br>基于加权向量空间模型的网络搜索*
%A BAI Xi
%A LV Xiao-feng
%A SUN Ji-gui
%A <br>白曦
%A 吕晓枫
%A 孙吉贵
%J 计算机应用研究
%D 2007
%I 
%X In order to train and categorize the articles more efficiently, which are obtained from Internet, this paper gives a new model of a classifier. This model applies the weighted factors of keywords on traditional Vector Space Model(VSM) and optimizes the characteristic vectors of articles when they have been trained. It can repair the weighted values of keywords and make the selection of the threshold value more convenient. The tests prove that this classifier which can categorize articles reasonably and more precisely also has the learning capacity.
%K Vector Space Model(VSM)
%K Automatic Categorization
%K Weighted Factor
%K Poundage Factor
%K Threshold Value<br>向量空间模型
%K 自动分类
%K 加权因子
%K 调节系数
%K 阈值
%K 加权向量
%K 空间模型
%K 网络搜索
%K Vector
%K Space
%K Model
%K Weighted
%K Based
%K Search
%K 学习功能
%K 分类准确性
%K 实验
%K 选取
%K 阈值
%K 权值
%K 恢复
%K 程度
%K 动态优化
%K 特征向量
%K 文档类型
%K 文档过程
%K 加权因子
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=343459AF1736CA69983B1B425655D09B&yid=A732AF04DDA03BB3&vid=B91E8C6D6FE990DB&iid=0B39A22176CE99FB&sid=987EDA49D8A7A635&eid=8E6AB9C3EBAAE921&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=5&reference_num=6