Abstract
This paper presents our contribution to the ProfNER shared task. Our work focused on evaluating different pre-trained word embedding representations suitable for the task. We further explored combinations of embeddings in order to improve the overall results.- Anthology ID:
- 2021.smm4h-1.27
- 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:
- 128–130
- Language:
- URL:
- https://aclanthology.org/2021.smm4h-1.27
- DOI:
- 10.18653/v1/2021.smm4h-1.27
- Bibkey:
- Cite (ACL):
- Vasile Pais and Maria Mitrofan. 2021. Assessing multiple word embeddings for named entity recognition of professions and occupations in health-related social media. In Proceedings of the Sixth Social Media Mining for Health (#SMM4H) Workshop and Shared Task, pages 128–130, Mexico City, Mexico. Association for Computational Linguistics.
- Cite (Informal):
- Assessing multiple word embeddings for named entity recognition of professions and occupations in health-related social media (Pais & Mitrofan, SMM4H 2021)
- Copy Citation:
- PDF:
- https://aclanthology.org/2021.smm4h-1.27.pdf
Export citation
@inproceedings{pais-mitrofan-2021-assessing,
title = "Assessing multiple word embeddings for named entity recognition of professions and occupations in health-related social media",
author = "Pais, Vasile and
Mitrofan, Maria",
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-1.27",
doi = "10.18653/v1/2021.smm4h-1.27",
pages = "128--130",
abstract = "This paper presents our contribution to the ProfNER shared task. Our work focused on evaluating different pre-trained word embedding representations suitable for the task. We further explored combinations of embeddings in order to improve the overall results.",
}
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%0 Conference Proceedings %T Assessing multiple word embeddings for named entity recognition of professions and occupations in health-related social media %A Pais, Vasile %A Mitrofan, Maria %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 pais-mitrofan-2021-assessing %X This paper presents our contribution to the ProfNER shared task. Our work focused on evaluating different pre-trained word embedding representations suitable for the task. We further explored combinations of embeddings in order to improve the overall results. %R 10.18653/v1/2021.smm4h-1.27 %U https://aclanthology.org/2021.smm4h-1.27 %U https://doi.org/10.18653/v1/2021.smm4h-1.27 %P 128-130
Markdown (Informal)
[Assessing multiple word embeddings for named entity recognition of professions and occupations in health-related social media](https://aclanthology.org/2021.smm4h-1.27) (Pais & Mitrofan, SMM4H 2021)
- Assessing multiple word embeddings for named entity recognition of professions and occupations in health-related social media (Pais & Mitrofan, SMM4H 2021)
ACL
- Vasile Pais and Maria Mitrofan. 2021. Assessing multiple word embeddings for named entity recognition of professions and occupations in health-related social media. In Proceedings of the Sixth Social Media Mining for Health (#SMM4H) Workshop and Shared Task, pages 128–130, Mexico City, Mexico. Association for Computational Linguistics.