A wordnet-based approach to feature selection in text categorization

Abstract

This paper proposes a new feature selection method for text categorization. In this method, word tendency, which takes related words into consideration, is used to select best terms. Our experiments on binary classification tasks show that our method achieves better than DF and IG when the classes are semantically discriminative. Furthermore, our best performance is usually achieved in fewer features. © 2005 by International Federation for Information Processing.