Practical Applications of ChatGPT and BERT: Long Text Summarization and Model Feature Ablation Study for Stock Comment Topic Identification-Reference-Cited by-同舟云学术

Practical Applications of ChatGPT and BERT: Long Text Summarization and Model Feature Ablation Study for Stock Comment Topic Identification

Published:2024-01-19 Issue: Volume: Page:787-793
ISSN:
Container-title:Proceedings of the 2024 Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Digital Economy and Artificial Intelligence
language:
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Author:

Xu Mingyan¹^ORCID,Chen Hongyu²^ORCID,Deng Fuwen³^ORCID,Liu Yuan³^ORCID,Zhao Feng⁴^ORCID,Zhang Yong⁵^ORCID

Affiliation:

1. School of Statistics, Shandong Technology and Business University, China

2. School of Hospital, Shandong Technology and Business University, China

3. School of Computer Science and Technology, Shandong Technology and Business University, China

4. Yantai Key Laboratory of Big Data Modeling and Intelligent Computing, China and School of Computer Science and Technology, Shandong Technology and Business University, China

5. School of Information and Electrotic, Shandong Technology and Business University, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3675417.3675549

Reference17 articles.

1. Bhat, I.K., Mohd, M. and Hashmy, R. 2018. SumItUp: A Hybrid Single-Document Text Summarizer. Soft Computing: Theories and Applications (Singapore, 2018), 619–634.

2. Devlin, J., Chang, M.-W., Lee, K. and Toutanova, K. 2018. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805. (2018).

3. Ding M. Zhou C. Yang H. and Tang J. 2020. CogLTX: Applying BERT to Long Texts. Advances in Neural Information Processing Systems (2020) 12792–12804.

4. Semi-supervised learning with generative model for sentiment classification of stock messages

5. Automatic text summarization: A comprehensive survey