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文本分类中的特征降维方法综述 被引量：79

Literature Review of Feature Dimension Reduction in Text Categorization
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摘要 文本分类的关键是对高维的特征集进行降维.降维的主要方法是特征选择和特征提取.本文综述了已有的特征选择和特征抽取方法,评价了它们的优缺点和适用范围. The key to text categorization is how to reduce the high-dimension of the feature vectors. Feature reduction method involves feature selection and feature extraction. In this paper feature selection methods and feature extraction methods are colligated. Their advantage and disadvantage are evaluated.
作者 陈涛 谢阳群
机构地区 宁波大学商学院信息管理系
出处 《情报学报》 CSSCI 北大核心 2005年第6期690-695,共6页 Journal of the China Society for Scientific and Technical Information
基金 浙江省教育厅资助项目
关键词 文本分类 特征降维 特征选择 特征提取 text categorization, feature reduction, feature selection, feature extraction.
分类号 TP391 [自动化与计算机技术—计算机应用技术] TP391.41 [自动化与计算机技术—计算机应用技术]
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参考文献25

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二级参考文献21

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共引文献239

同被引文献841

引证文献79

二级引证文献335

情报学报
2005年 第6期

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