Text Classification Using WordNet Hypernyms

Abstract

This paper describes experiments in Machine Learning for text classification using a new representation of text based on WordNet hypemyms. Six binary classification tasks of varying difficulty are defined, and the Ripper system is used to produce discrimination rules for each task using the new hypernym density representation. Rules are also produced with the commonly used bag-of-words representation, incorporating no knowledge from WordNet. Experiments show