An empirical study of the domain dependence of supervised word sense disambiguation systems
Gerard Escudero, Lluı́s Màrquez, Germán Rigau · 2000
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.