关键词: 文本分类, 特征选择, 特征加权, 基尼指数

Abstract: The aim of feature selection and weighting in automatic text categorization is to reduce the dimension of feature space，remove noise features and improve classification precision.The features selected by traditional feature selection methods always bias common category，and the commonly used weighting method TF*IDF only considers the relationship between features and documents and ignores the relationship between features and categories.According to the above problem，this paper presents a text feature selection and weighting method based on category.Experiments on skewed category distribution corpus of two different languages show that the method can improve categorization precision effectively，and comparing with traditional method，the feature space dimension is also reduced to a certain degree.

Key words: text categorization, feature selection, feature weighting, Gini-Index