Classification, Extraction, and Normalization : CASIA_Unisound Team at the Social Media Mining for Health 2021 Shared Tasks
Tong Zhou, Zhucong Li, Zhen Gan, Baoli Zhang, Yubo Chen, Kun Niu, Jing Wan, Kang Liu, Jun Zhao, Yafei Shi, Weifeng Chong, Shengping Liu
Correct Metadata for
Abstract
This is the system description of the CASIA_Unisound team for Task 1, Task 7b, and Task 8 of the sixth Social Media Mining for Health Applications (SMM4H) shared task in 2021. Targeting on deal with two shared challenges, the colloquial text and the imbalance annotation, among those tasks, we apply a customized pre-trained language model and propose various training strategies. Experimental results show the effectiveness of our system. Moreover, we got an F1-score of 0.87 in task 8, which is the highest among all participates.- Anthology ID:
- 2021.smm4h-1.13
- Volume:
- Proceedings of the Sixth Social Media Mining for Health (#SMM4H) Workshop and Shared Task
- Month:
- June
- Year:
- 2021
- Address:
- Mexico City, Mexico
- Editors:
- Arjun Magge, Ari Klein, Antonio Miranda-Escalada, Mohammed Ali Al-garadi, Ilseyar Alimova, Zulfat Miftahutdinov, Eulalia Farre-Maduell, Salvador Lima Lopez, Ivan Flores, Karen O'Connor, Davy Weissenbacher, Elena Tutubalina, Abeed Sarker, Juan M Banda, Martin Krallinger, Graciela Gonzalez-Hernandez
- Venue:
- SMM4H
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 77–82
- Language:
- URL:
- https://aclanthology.org/2021.smm4h-1.13/
- DOI:
- 10.18653/v1/2021.smm4h-1.13
- Bibkey:
- Cite (ACL):
- Tong Zhou, Zhucong Li, Zhen Gan, Baoli Zhang, Yubo Chen, Kun Niu, Jing Wan, Kang Liu, Jun Zhao, Yafei Shi, Weifeng Chong, and Shengping Liu. 2021. Classification, Extraction, and Normalization : CASIA_Unisound Team at the Social Media Mining for Health 2021 Shared Tasks. In Proceedings of the Sixth Social Media Mining for Health (#SMM4H) Workshop and Shared Task, pages 77–82, Mexico City, Mexico. Association for Computational Linguistics.
- Cite (Informal):
- Classification, Extraction, and Normalization : CASIA_Unisound Team at the Social Media Mining for Health 2021 Shared Tasks (Zhou et al., SMM4H 2021)
- Copy Citation:
- PDF:
- https://aclanthology.org/2021.smm4h-1.13.pdf
Export citation
@inproceedings{zhou-etal-2021-classification,
title = "Classification, Extraction, and Normalization : {CASIA}{\_}{U}nisound Team at the Social Media Mining for Health 2021 Shared Tasks",
author = "Zhou, Tong and
Li, Zhucong and
Gan, Zhen and
Zhang, Baoli and
Chen, Yubo and
Niu, Kun and
Wan, Jing and
Liu, Kang and
Zhao, Jun and
Shi, Yafei and
Chong, Weifeng and
Liu, Shengping",
editor = "Magge, Arjun and
Klein, Ari and
Miranda-Escalada, Antonio and
Al-garadi, Mohammed Ali and
Alimova, Ilseyar and
Miftahutdinov, Zulfat and
Farre-Maduell, Eulalia and
Lopez, Salvador Lima and
Flores, Ivan and
O'Connor, Karen and
Weissenbacher, Davy and
Tutubalina, Elena and
Sarker, Abeed and
Banda, Juan M and
Krallinger, Martin and
Gonzalez-Hernandez, Graciela",
booktitle = "Proceedings of the Sixth Social Media Mining for Health ({\#}SMM4H) Workshop and Shared Task",
month = jun,
year = "2021",
address = "Mexico City, Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.smm4h-1.13/",
doi = "10.18653/v1/2021.smm4h-1.13",
pages = "77--82",
abstract = "This is the system description of the CASIA{\_}Unisound team for Task 1, Task 7b, and Task 8 of the sixth Social Media Mining for Health Applications (SMM4H) shared task in 2021. Targeting on deal with two shared challenges, the colloquial text and the imbalance annotation, among those tasks, we apply a customized pre-trained language model and propose various training strategies. Experimental results show the effectiveness of our system. Moreover, we got an F1-score of 0.87 in task 8, which is the highest among all participates."
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%0 Conference Proceedings %T Classification, Extraction, and Normalization : CASIA_Unisound Team at the Social Media Mining for Health 2021 Shared Tasks %A Zhou, Tong %A Li, Zhucong %A Gan, Zhen %A Zhang, Baoli %A Chen, Yubo %A Niu, Kun %A Wan, Jing %A Liu, Kang %A Zhao, Jun %A Shi, Yafei %A Chong, Weifeng %A Liu, Shengping %Y Magge, Arjun %Y Klein, Ari %Y Miranda-Escalada, Antonio %Y Al-garadi, Mohammed Ali %Y Alimova, Ilseyar %Y Miftahutdinov, Zulfat %Y Farre-Maduell, Eulalia %Y Lopez, Salvador Lima %Y Flores, Ivan %Y O’Connor, Karen %Y Weissenbacher, Davy %Y Tutubalina, Elena %Y Sarker, Abeed %Y Banda, Juan M. %Y Krallinger, Martin %Y Gonzalez-Hernandez, Graciela %S Proceedings of the Sixth Social Media Mining for Health (#SMM4H) Workshop and Shared Task %D 2021 %8 June %I Association for Computational Linguistics %C Mexico City, Mexico %F zhou-etal-2021-classification %X This is the system description of the CASIA_Unisound team for Task 1, Task 7b, and Task 8 of the sixth Social Media Mining for Health Applications (SMM4H) shared task in 2021. Targeting on deal with two shared challenges, the colloquial text and the imbalance annotation, among those tasks, we apply a customized pre-trained language model and propose various training strategies. Experimental results show the effectiveness of our system. Moreover, we got an F1-score of 0.87 in task 8, which is the highest among all participates. %R 10.18653/v1/2021.smm4h-1.13 %U https://aclanthology.org/2021.smm4h-1.13/ %U https://doi.org/10.18653/v1/2021.smm4h-1.13 %P 77-82
Markdown (Informal)
[Classification, Extraction, and Normalization : CASIA_Unisound Team at the Social Media Mining for Health 2021 Shared Tasks](https://aclanthology.org/2021.smm4h-1.13/) (Zhou et al., SMM4H 2021)
- Classification, Extraction, and Normalization : CASIA_Unisound Team at the Social Media Mining for Health 2021 Shared Tasks (Zhou et al., SMM4H 2021)
ACL
- Tong Zhou, Zhucong Li, Zhen Gan, Baoli Zhang, Yubo Chen, Kun Niu, Jing Wan, Kang Liu, Jun Zhao, Yafei Shi, Weifeng Chong, and Shengping Liu. 2021. Classification, Extraction, and Normalization : CASIA_Unisound Team at the Social Media Mining for Health 2021 Shared Tasks. In Proceedings of the Sixth Social Media Mining for Health (#SMM4H) Workshop and Shared Task, pages 77–82, Mexico City, Mexico. Association for Computational Linguistics.