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A deep learning approach to bilingual lexicon induction in the biomedical domain. ...
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Abstract:
BACKGROUND: Bilingual lexicon induction (BLI) is an important task in the biomedical domain as translation resources are usually available for general language usage, but are often lacking in domain-specific settings. In this article we consider BLI as a classification problem and train a neural network composed of a combination of recurrent long short-term memory and deep feed-forward networks in order to obtain word-level and character-level representations. RESULTS: The results show that the word-level and character-level representations each improve state-of-the-art results for BLI and biomedical translation mining. The best results are obtained by exploiting the synergy between these word-level and character-level representations in the classification model. We evaluate the models both quantitatively and qualitatively. CONCLUSIONS: Translation of domain-specific biomedical terminology benefits from the character-level representations compared to relying solely on word-level representations. It is ...
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Keyword:
Data Mining; Deep Learning; Humans; Knowledge Bases; Multilingualism; Natural Language Processing; Semantics
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URL: https://dx.doi.org/10.17863/cam.36243 https://www.repository.cam.ac.uk/handle/1810/288980
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A deep learning approach to bilingual lexicon induction in the biomedical domain.
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