An improved data augmentation approach and its application in medical named entity recognition

Author:

Chen Hongyu,Dan Li,Lu Yonghe,Chen Minghong,Zhang Jinxia

Funder

Guangzhou Science and Technology Planning Project

Publisher

Springer Science and Business Media LLC

Reference72 articles.

1. Chieu HL, Ng HT. Named Entity Recognition: a maximum entropy approach using global information. In: Proceedings of the 19th international conference on computational linguistics. Morristown: Association for Computational Linguistics; 2002.

2. Levow GA. The third international chinese language processing bakeoff: word segmentation and named entity recognition. In: Proceedings of the Fifth SIGHAN Workshop on Chinese Language Processing. Sydney: Association for Computational Linguistics; 2006. p. 108–17.

3. Makridakis S, Spiliotis E, Assimakopoulos V. Statistical and machine learning forecasting methods: concerns and ways forward. PLoS One. 2018;13(3):e0194889.

4. Krizhevsky A, Sutskever I, Hinton GE. ImageNet Classification with Deep Convolutional Neural Networks. Commun ACM. 2017;60(6):84–90.

5. Yadav V, Bethard S. A survey on recent advances in named entity recognition from deep learning models. arXiv [cs.CL]. 2019. 1910.11470.

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