Combination methods are an effective way of improving system performance. This paper examines the benefits of system combination for unsupervised WSD. We investigate several voting- and arbiter-based combination strategies over a diverse pool of unsupervised WSD systems. Our combination methods rely on predominant senses which are derived automatically from raw text. Experiments using the SemCor and Senseval-3 data sets demonstrate that our ensembles yield significantly better results when compared with state-of-the-art.
Ensemble Methods for Unsupervised WSD / S., Brody; Navigli, Roberto; M., Lapata. - STAMPA. - (2006), pp. 97-104. (Intervento presentato al convegno COLING-ACL 2006 tenutosi a Sydney, Australia nel July 17-21st, 2006).
Ensemble Methods for Unsupervised WSD
NAVIGLI, ROBERTO;
2006
Abstract
Combination methods are an effective way of improving system performance. This paper examines the benefits of system combination for unsupervised WSD. We investigate several voting- and arbiter-based combination strategies over a diverse pool of unsupervised WSD systems. Our combination methods rely on predominant senses which are derived automatically from raw text. Experiments using the SemCor and Senseval-3 data sets demonstrate that our ensembles yield significantly better results when compared with state-of-the-art.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
