Abstract
In this paper, we experiment with several techniques to solve the problem of lexical substitution, both in alexical sampleas well as anall-wordssetting, and compare the benefits of combining multiple lexical resources using both unsupervised and supervised approaches. Overall in the lexical sample setting, the results obtained through the combination of several resources exceed the current state-of-the-art when selecting the best substitute for a given target word, and place second when selecting the top ten substitutes, thus demonstrating the usefulness of the approach. Further, we put forth a novel exploration in all-words lexical substitution and set ground for further explorations of this more generalized setting.
Publisher
Cambridge University Press (CUP)
Subject
Artificial Intelligence,Linguistics and Language,Language and Linguistics,Software
Cited by
2 articles.
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