Neural sentence embedding models for semantic similarity estimation in the biomedical domain

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...

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Bibliographic Details
Main Authors: Kathrin Blagec, Hong Xu, Asan Agibetov, Matthias Samwald
Format: Article
Language:English
Published: BMC 2019-04-01
Series:BMC Bioinformatics
Subjects:
Natural language processing
Semantics
Neural embedding models
Online Access:http://link.springer.com/article/10.1186/s12859-019-2789-2

Internet

http://link.springer.com/article/10.1186/s12859-019-2789-2

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