关键词: 文本分类, 特征选择, 类内集中度, 分层递阶约简

Abstract: Feature selection is one of the key steps in text categorization.The selected feature subset directly influences results of text categorization.It firstly analyzes simply several classic feature selection methods and summarizes their deficiencies，and then presents the concept of classificatory concentration，next introduces thoughts of hierarchical reduction into rough sets and provides an improved hierarchical reduction algorithm，finally，combines the reduction algorithm with the classificatory concentration and proposes a comprehensive feature selection method.The comprehensive method firstly uses the classificatory concentration to select feature and filter out some terms to reduce the sparsity of feature spaces，and then uses the hierarchical reduction algorithm to eliminate redundancy，so can acquire the feature subset which are more representative.The experimental results show that the comprehensive method is promising.

Key words: text categorization, feature selection, classificatory concentration, hierarchical reduction