LSTMVoter: chemical named entity recognition using a conglomerate of sequence labeling tools

LSTMVoter: chemical named entity recognition using a conglomerate of sequence labeling tools

Abstract Background Chemical and biomedical named entity recognition (NER) is an essential preprocessing task in natural language processing. The identification and extraction of named entities from scientific articles is also attracting increasing interest in many scientific disciplines. Locating c...

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Bibliographic Details
Main Authors: Wahed Hemati, Alexander Mehler
Format: Article
Language:English
Published: BMC 2019-01-01
Series:Journal of Cheminformatics
Subjects:
BioCreative V.5
CEMP
CHEMDNER
BioNLP
Named entity recognition
Deep learning
Online Access:http://link.springer.com/article/10.1186/s13321-018-0327-2

Internet

http://link.springer.com/article/10.1186/s13321-018-0327-2

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