dezzai@SMM4H’22: Tasks 5 & 10 - Hybrid models everywhere
Miguel Ortega-Martín, Alfonso Ardoiz, Oscar Garcia, Jorge Álvarez, Adrián Alonso
Abstract
This paper presents our approaches to SMM4H’22 task 5 - Classification of tweets of self-reported COVID-19 symptoms in Spanish, and task 10 - Detection of disease mentions in tweets – SocialDisNER (in Spanish). We have presented hybrid systems that combine Deep Learning techniques with linguistic rules and medical ontologies, which have allowed us to achieve outstanding results in both tasks.- Anthology ID:
- 2022.smm4h-1.3
- 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:
- 7–10
- Language:
- URL:
- https://aclanthology.org/2022.smm4h-1.3
- DOI:
- Cite (ACL):
- Miguel Ortega-Martín, Alfonso Ardoiz, Oscar Garcia, Jorge Álvarez, and Adrián Alonso. 2022. dezzai@SMM4H’22: Tasks 5 & 10 - Hybrid models everywhere. In Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop & Shared Task, pages 7–10, Gyeongju, Republic of Korea. Association for Computational Linguistics.
- Cite (Informal):
- dezzai@SMM4H’22: Tasks 5 & 10 - Hybrid models everywhere (Ortega-Martín et al., SMM4H 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2022.smm4h-1.3.pdf