Looking for Hyponyms in Vector Space.
Eighteenth Conference on Computational Natural Language Learning
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Rei, M., & Briscoe, E. (2014). Looking for Hyponyms in Vector Space.. CoNLL, 68-77. http://www.aclweb.org/anthology/K/K14/#2014_0
The task of detecting and generating hyponyms is at the core of semantic understanding of language, and has numerous practical applications. We investigate how neural network embeddings perform on this task, compared to dependency-based vector space models, and evaluate a range of similarity measures on hyponym generation. A new asymmetric similarity measure and a combination approach are described, both of which significantly improve precision. We release three new datasets of lexical vector representations trained on the BNC and our evaluation dataset for hyponym generation.
External link: http://www.aclweb.org/anthology/K/K14/#2014_0
This record's URL: https://www.repository.cam.ac.uk/handle/1810/294973