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Exploring patterns in dictionary definitions for synonym extraction

Published online by Cambridge University Press:  11 July 2011

TONG WANG
Affiliation:
Department of Computer Science, University of Toronto, Toronto, ON M5S 3G4, Canada e-mail: tong@cs.toronto.edu, gh@cs.toronto.edu
GRAEME HIRST
Affiliation:
Department of Computer Science, University of Toronto, Toronto, ON M5S 3G4, Canada e-mail: tong@cs.toronto.edu, gh@cs.toronto.edu

Abstract

Automatic determination of synonyms and/or semantically related words has various applications in Natural Language Processing. Two mainstream paradigms to date, lexicon-based and distributional approaches, both exhibit pros and cons with regard to coverage, complexity, and quality. In this paper, we propose three novel methods—two rule-based methods and one machine learning approach—to identify synonyms from definition texts in a machine-readable dictionary. Extracted synonyms are evaluated in two extrinsic experiments and one intrinsic experiment. Evaluation results show that our pattern-based approach achieves best performance in one of the experiments and satisfactory results in the other, comparable to corpus-based state-of-the-art results.

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Articles
Copyright
Copyright © Cambridge University Press 2011

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