Exploiting Thesaurus Knowledge in Rule Induction for Text Classiication

Systems for learning text classiiers recently gained considerable interest. One technique to implement such systems is rule induction. While most other approaches rely on a relatively simple document representation and do not make use of any background knowledge, rule induction algorithms ooer a good potential for improvements in both of these areas. In this paper , we show how an operator-based view of rule induction enables the easy integration of a thesaurus as background knowledge. Results with an algorithm extended by thesaurus knowledge are presented and interpreted. The interpretation shows the strengths and weaknesses of using thesaurus knowledge and gives hints for future research.