关键词: 文本分类, 特征选择, 信息增益

Abstract: High dimensionality is one of the main problems in text categorization.Feature selection methods can be regarded as an effective way.Main feature selection methods are document frequency，information gain，mutual information，and so on.This paper improves a new feature selection method SIG based on TTC and a universal method for developing feature selection functions.This method emphasizes the terms with middle and low frequencies and gets a good classification performance.Experiments on Reuters-21578 collection imply that this method is effective and can make better use of the terms with middle and low frequencies.

Key words: text categorization, feature selection, information gain