Learning taxonomical relations from domain texts using WordNet and word sense disambiguation
Document Type
Conference Proceeding
Publication Date
12-1-2012
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. © 2012 IEEE.
Publication Source (Journal or Book title)
Proceedings - 2012 IEEE International Conference on Granular Computing, GrC 2012
First Page
382
Last Page
387
Recommended Citation
Punuru, J., & Chen, J. (2012). Learning taxonomical relations from domain texts using WordNet and word sense disambiguation. Proceedings - 2012 IEEE International Conference on Granular Computing, GrC 2012, 382-387. https://doi.org/10.1109/GrC.2012.6468601