Abstract
CLaC labs participated in Task 1 and 4 of SMM4H 2019. We pursed two main objectives in our submission. First we tried to use some textual features in a deep net framework, and second, the potential use of more than one word embedding was tested. The results seem positively affected by the proposed architectures.- Anthology ID:
- W19-3222
- Volume:
- Proceedings of the Fourth Social Media Mining for Health Applications (#SMM4H) Workshop & Shared Task
- Month:
- August
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Davy Weissenbacher, Graciela Gonzalez-Hernandez
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 123–126
- Language:
- URL:
- https://aclanthology.org/W19-3222
- DOI:
- 10.18653/v1/W19-3222
- Cite (ACL):
- Parsa Bagherzadeh, Nadia Sheikh, and Sabine Bergler. 2019. Adverse Drug Effect and Personalized Health Mentions, CLaC at SMM4H 2019, Tasks 1 and 4. In Proceedings of the Fourth Social Media Mining for Health Applications (#SMM4H) Workshop & Shared Task, pages 123–126, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- Adverse Drug Effect and Personalized Health Mentions, CLaC at SMM4H 2019, Tasks 1 and 4 (Bagherzadeh et al., ACL 2019)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-5/W19-3222.pdf
- Data
- SMM4H