---
title: "Optimizing Classifier Performance in Word Sense Disambiguation by Redefining Sense Classes"
authors:
  - "Upali Sathyajith Kohomban"
  - "Wee Sun Lee"
doi: ""
url: "https://ijcai.org/proceedings/2007/264"
pdf: "https://ijcai.org/proceedings/2007/0264.pdf"
venue: "Proceedings of the Twentieth International Joint Conference on Artificial Intelligence"
year: 2007
pages: "1635-1639"
track: ""
keywords:
---

# Optimizing Classifier Performance in Word Sense Disambiguation by Redefining Sense Classes

Upali Sathyajith Kohomban, Wee Sun Lee

*Proceedings of the Twentieth International Joint Conference on Artificial Intelligence*, pages 1635-1639.

## Abstract

Learning word sense classes has been shown to be useful in fine-grained word sense disambiguation. However, the common choice for sense classes, WordNet lexicographer files, are not designed for machine learning based word sense disambiguation. In this work, we explore the use of clustering techniques in an effort to construct sense classes that are more suitable for word sense disambiguation end-task. Our results show that these classes can significantly improve classifier performance over the state of the art results of unrestricted word sense disambiguation.