Gerard Escudero
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.
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- An empirical study of the domain dependence of supervised word sense disambiguation systems
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