Year: 2001
Type: conference-paper
Abstract: We report on the use of machine learning techniques for word sense disambiguation in the English all words task of SENSEVAL2. The task was to automatically assign the appropriate sense to a possibly ambiguous word form given its context. A "word expert" approach was adopted, leading to a set of classifiers, each specialized in one single word form-POS combination. Experts consist of multiple classifiers trained on Semcor using two types of learning techniques, viz. memory-based learning and rule-induction. Through optimization by cross-validation of the individual classifiers and the voting scheme for combining them, the best possible word expert was determined. Results show that especially memory-based learning in a word-expert approach is a feasible method for unrestricted word-sense disambiguation, even with limited training data.
Authors: Véronique Hoste, Anne Kool, Walter Daelemans
Institution: University of Antwerp
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W142000222