Learning to distinguish hypernyms and co-hyponyms

Weeds, Julie, Clarke, Daoud, Reffin, Jeremy, Weir, David and Keller, Bill (2014) Learning to distinguish hypernyms and co-hyponyms. Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers. pp. 2249-2259.

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Abstract

This work is concerned with distinguishing different semantic relations which exist between distributionally similar words. We compare a novel approach based on training a linear Support Vector Machine on pairs of feature vectors with state-of-the-art methods based on distributional similarity. We show that the new supervised approach does better even when there is minimal information about the target words in the training data, giving a 15% reduction in error rate over unsupervised approaches.

Item Type: Article
Schools and Departments: School of Engineering and Informatics > Informatics
Subjects: P Language and Literature > P Philology. Linguistics > P0098 Computational linguistics. Natural language processing
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Depositing User: Bill Keller
Date Deposited: 27 Feb 2015 09:05
Last Modified: 07 Mar 2017 06:41
URI: http://sro.sussex.ac.uk/id/eprint/53103

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