Multi-class multi-label classification of social media texts for typhoon damage assessment: a two-stage model fully integrating the outputs of the hidden layers of BERT-Reference-Cited by-同舟云学术

Multi-class multi-label classification of social media texts for typhoon damage assessment: a two-stage model fully integrating the outputs of the hidden layers of BERT

Published:2024-05-08 Issue:1 Volume:17 Page:
ISSN:1753-8947
Container-title:International Journal of Digital Earth
language:en
Short-container-title:International Journal of Digital Earth

Author:

Zou Liwei¹²,He Zhi¹²^ORCID,Zhou Chengle¹²,Zhu Wenbing¹²

Affiliation:

1. School of Geography and Planning, Sun Yat-sen University, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Guangzhou, People's Republic of China

2. Guangdong Provincial Key Laboratory of Intelligent Urban Security Monitoring and Smart City Planning, Guangzhou, People's Republic of China

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/17538947.2024.2348668

Reference35 articles.

1. IEEE Access

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3. Clark Kevin Minh-Thang Luong Quoc V. Le and Christopher D. Manning. 2020. “Electra: Pre-Training Text Encoders as Discriminators Rather Than Generators.” arXiv preprint arXiv:2003.10555: 1–18.

4. Dai Zhenjin Xutao Wang Pin Ni Yuming Li Gangmin Li and Xuming Bai. 2019. “Named Entity Recognition Using BERT BiLSTM CRF for Chinese Electronic Health Records.” In 2019 12th International Congress on Image and Signal Processing Biomedical Engineering and Informatics (CISP-BMEI) 1–5. IEEE.

5. Devlin Jacob Ming-Wei Chang Kenton Lee and Kristina Toutanova. 2018. “BERT: Pre-Training of Deep Bidirectional Transformers for Language Understanding.” arXiv preprint arXiv:1810.04805: 1–16.

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