A hybrid deep-learning approach for complex biochemical named entity recognition

Liu, Jian, Gao, Lei, Guo, Sujie, Ding, Rui, Huang, Xin, Ye, Long, Meng, Qinghua, Nazari, Asef and Thiruvady, Dhananjay 2021, A hybrid deep-learning approach for complex biochemical named entity recognition, Knowledge-based systems, pp. 1-23, doi: 10.1016/j.knosys.2021.106958.

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Title A hybrid deep-learning approach for complex biochemical named entity recognition
Author(s) Liu, Jian
Gao, Lei
Guo, Sujie
Ding, Rui
Huang, Xin
Ye, Long
Meng, Qinghua
Nazari, AsefORCID iD for Nazari, Asef orcid.org/0000-0003-4955-9684
Thiruvady, DhananjayORCID iD for Thiruvady, Dhananjay orcid.org/0000-0002-8011-933X
Journal name Knowledge-based systems
Article ID 106958
Start page 1
End page 23
Total pages 23
Publisher Elsevier
Place of publication Amsterdam, The Netherlands
Publication date 2021-03-22
ISSN 0950-7051
Keyword(s) Named entity recognition
Deep learning
Bi-directional long Short-Term Memory (BILSTM)
Conditional Random Field (CRF)
Bidirectional Encoder Representations from Transformers (BERT)
Multi-Head Attention (MHATT)
Notes Pre-proof
Language eng
DOI 10.1016/j.knosys.2021.106958
Indigenous content off
Field of Research 08 Information and Computing Sciences
15 Commerce, Management, Tourism and Services
17 Psychology and Cognitive Sciences
HERDC Research category C1 Refereed article in a scholarly journal
Persistent URL http://hdl.handle.net/10536/DRO/DU:30149453

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