Learning taxonomical relations from domain texts using WordNet and word sense disambiguation

  • Authors:
  • Janardhana Punuru;Jianhua Chen

  • Affiliations:
  • Department of Computer Science, Louisiana State University, Baton Rouge, 70803-4020, USA;Department of Computer Science, Louisiana State University, Baton Rouge, 70803-4020, USA

  • Venue:
  • GRC '12 Proceedings of the 2012 IEEE International Conference on Granular Computing (GrC-2012)
  • Year:
  • 2012

Quantified Score

Hi-index 0.00

Visualization

Abstract

Learning taxonomical relations from domain texts is an important task for ontology learning from texts. We observe that rich information on taxonomical relations is available in the lexical knowledge base WordNet. However, in order to exploit the taxonomical relations in WordNet we need to tackle the difficult problem of word sense disambiguation. In this paper, we present a weighted word sense disambiguation method and show its application for learninng taxonomical relations from domain texts. The experimental results indicate that using WordNet and our word sense disambiguation method achieves good accuracy and coverage for the learning task.