关键词: 文本分类, 特征选择, 语义, 知网

Abstract: The traditional selection methods for text categorization are based on the statistical information of word frequency, which ignores the semantic effect of the words and cannot take more useful features because of the redundancy. A table named "conception-domain" was built based on the semantic dictionary HowNet, which included the word itself and its domain value. If a word from the text was existent in the table, it would be replaced by its domain value with more general meaning. By this way, more semantic information was added to the selected features and the redundancy between features of items could be eliminated to some extent. The experiments were carried out by improved information gain and χ2 respectively. And the results show that this method has effectively improved the precision of the text categorization.

Key words: text categorization, feature selection, semantic, HowNet