An empirical study of the domain dependence of supervised word sense disambiguation systems

Authors:
Gerard Escudero;Lluís Màrquez;German Rigau
Affiliations:
Universitat Politècnica de Catalunya (UPC), Barcelona, Catalonia;Universitat Politècnica de Catalunya (UPC), Barcelona, Catalonia;Universitat Politècnica de Catalunya (UPC), Barcelona, Catalonia
Venue:
EMNLP '00 Proceedings of the 2000 Joint SIGDAT conference on Empirical methods in natural language processing and very large corpora: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 13
Year:
2000

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Abstract

This paper describes a set of experiments carried out to explore the domain dependence of alternative supervised Word Sense Disambiguation algorithms. The aim of the work is threefold: studying the performance of these algorithms when tested on a different corpus from that they were trained on; exploring their ability to tune to new domains, and demonstrating empirically that the Lazy-Boosting algorithm outperforms state-of-the-art supervised WSD algorithms in both previous situations.