Metodebevisregistrering
Domain-adaptive Named Entity Recognition
Domain-adaptive Named Entity Recognition (DA-NER) applies named entity recognition to a target domain by transferring or adapting a model trained on a source domain, using techniques such as domain-specific pre-training, adversarial alignment, or feature augmentation. It addresses the performance collapse that standard NER models suffer when deployed outside their training domain.
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Domain-adaptive Named Entity Recognition (DA-NER)
Taksonomisk metoderegistrering · ml-model / deep-learning
- Lee, J., Yoon, W., Kim, S., Kim, D., Kim, S., So, C. H., & Kang, J. (2020). BioBERT: a pre-trained biomedical language representation model for biomedical text mining. Bioinformatics, 36(4), 1234–1240. · DOI 10.1093/bioinformatics/btz682
- Blitzer, J., McDonald, R., & Pereira, F. (2006). Domain adaptation with structural correspondence learning. Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing (EMNLP), 120–128. · URL
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