CASIA@SMM4H’22: A Uniform Health Information Mining System for Multilingual Social Media Texts
Jia Fu, Sirui Li, Hui Ming Yuan, Zhucong Li, Zhen Gan, Yubo Chen, Kang Liu, Jun Zhao, Shengping Liu
Abstract
This paper presents a description of our system in SMM4H-2022, where we participated in task 1a,task 4, and task 6 to task 10. There are three main challenges in SMM4H-2022, namely the domain shift problem, the prediction bias due to category imbalance, and the noise in informal text. In this paper, we propose a unified framework for the classification and named entity recognition tasks to solve the challenges, and it can be applied to both English and Spanish scenarios. The results of our system are higher than the median F1-scores for 7 tasks and significantly exceed the F1-scores for 6 tasks. The experimental results demonstrate the effectiveness of our system.- Anthology ID:
- 2022.smm4h-1.39
- Volume:
- Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop & Shared Task
- Month:
- October
- Year:
- 2022
- Address:
- Gyeongju, Republic of Korea
- Editors:
- Graciela Gonzalez-Hernandez, Davy Weissenbacher
- Venue:
- SMM4H
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 143–147
- Language:
- URL:
- https://aclanthology.org/2022.smm4h-1.39
- DOI:
- Cite (ACL):
- Jia Fu, Sirui Li, Hui Ming Yuan, Zhucong Li, Zhen Gan, Yubo Chen, Kang Liu, Jun Zhao, and Shengping Liu. 2022. CASIA@SMM4H’22: A Uniform Health Information Mining System for Multilingual Social Media Texts. In Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop & Shared Task, pages 143–147, Gyeongju, Republic of Korea. Association for Computational Linguistics.
- Cite (Informal):
- CASIA@SMM4H’22: A Uniform Health Information Mining System for Multilingual Social Media Texts (Fu et al., SMM4H 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/2022.smm4h-1.39.pdf