Neural sentence embedding models for semantic similarity estimation in the biomedical domain
Abstract Background Neural network based embedding models are receiving significant attention in the field of natural language processing due to their capability to effectively capture semantic information representing words, sentences or even larger text elements in low-dimensional vector space. Wh...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2019-04-01
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| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12859-019-2789-2 |