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.", }
<?xml version="1.0" encoding="UTF-8"?> <modsCollection xmlns="http://www.loc.gov/mods/v3"> <mods ID="pais-mitrofan-2021-assessing"> <titleInfo> <title>Assessing multiple word embeddings for named entity recognition of professions and occupations in health-related social media</title> </titleInfo> <name type="personal"> <namePart type="given">Vasile</namePart> <namePart type="family">Pais</namePart> <role> <roleTerm authority="marcrelator" type="text">author</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Maria</namePart> <namePart type="family">Mitrofan</namePart> <role> <roleTerm authority="marcrelator" type="text">author</roleTerm> </role> </name> <originInfo> <dateIssued>2021-06</dateIssued> </originInfo> <typeOfResource>text</typeOfResource> <relatedItem type="host"> <titleInfo> <title>Proceedings of the Sixth Social Media Mining for Health (#SMM4H) Workshop and Shared Task</title> </titleInfo> <name type="personal"> <namePart type="given">Arjun</namePart> <namePart type="family">Magge</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Ari</namePart> <namePart type="family">Klein</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Antonio</namePart> <namePart type="family">Miranda-Escalada</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Mohammed</namePart> <namePart type="given">Ali</namePart> <namePart type="family">Al-garadi</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Ilseyar</namePart> <namePart type="family">Alimova</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Zulfat</namePart> <namePart type="family">Miftahutdinov</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Eulalia</namePart> <namePart type="family">Farre-Maduell</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Salvador</namePart> <namePart type="given">Lima</namePart> <namePart type="family">Lopez</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Ivan</namePart> <namePart type="family">Flores</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Karen</namePart> <namePart type="family">O’Connor</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Davy</namePart> <namePart type="family">Weissenbacher</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Elena</namePart> <namePart type="family">Tutubalina</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Abeed</namePart> <namePart type="family">Sarker</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Juan</namePart> <namePart type="given">M</namePart> <namePart type="family">Banda</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Martin</namePart> <namePart type="family">Krallinger</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Graciela</namePart> <namePart type="family">Gonzalez-Hernandez</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <originInfo> <publisher>Association for Computational Linguistics</publisher> <place> <placeTerm type="text">Mexico City, Mexico</placeTerm> </place> </originInfo> <genre authority="marcgt">conference publication</genre> </relatedItem> <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.</abstract> <identifier type="citekey">pais-mitrofan-2021-assessing</identifier> <identifier type="doi">10.18653/v1/2021.smm4h-1.27</identifier> <location> <url>https://aclanthology.org/2021.smm4h-1.27</url> </location> <part> <date>2021-06</date> <extent unit="page"> <start>128</start> <end>130</end> </extent> </part> </mods> </modsCollection>
%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.