Parallel sequence tagging for concept recognition

Parallel sequence tagging for concept recognition

Background: Named Entity Recognition (NER) and Normalisation (NEN) are core components of any text-mining system for biomedical texts. In a traditional concept-recognition pipeline, these tasks are combined in a serial way, which is inherently prone to error propagation from NER to NEN. We propose a...

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Bibliographic Details
Main Authors: Cornelius, J. (Author), Furrer, L. (Author), Rinaldi, F. (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2021
Subjects:
article
Backpropagation
calibration
Character recognition
classifier
competition
Concept recognition
Core components
data mining
Data mining
Data Mining
Economic and social effects
Harmonisation
mining
Mining systems
molecular recognition
Named entity normalizations
Named entity recognition
Named entity recognition and normalization
Natural language processing systems
Neural network
Neural-networks
Normalisation
Parallel architectures
pipeline
Pipelines
prediction
Sequence tagging
Text mining
Text processing
Text-mining
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