Machine Learning with Lexical Features: The Duluth Approach to Senseval-2

Thumbnail Image

Date

Authors

Journal Title

Journal ISSN

Volume Title

Publisher

Abstract

Description

This paper describes the sixteen Duluth entries in the Senseval-2 comparative exercise among word sense disambiguation systems. There were eight pairs of Duluth systems entered in the Spanish and English lexical sample tasks. These are all based on standard machine learning algorithms that induce classifiers from sense-tagged training text where the context in which ambiguous words occur are represented by simple lexical features. These are highly portable, robust methods that can serve as a foundation for more tailored approaches.
Appears in the Proceedings of SENSEVAL-2: Second International Workshop on Evaluating Word Sense Disambiguation Systems July 5-6, 2001, Toulouse, France

Keywords

Computation and Language, I.2.7

Citation

URI

http://salesiana.dossiersoluciones.com/handle/123456789/31120

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/cs/0205069
 http://arxiv.org/abs/cs/0205069

Collections

arXiv