@inproceedings{montanes-salas-etal-2022-itainnova,
title = "{ITAINNOVA} at {S}ocial{D}is{NER}: A Transformers cocktail for disease identification in social media in {S}panish",
author = "Monta{\~n}{\'e}s-Salas, Rosa and
L{\'o}pez-Bosque, Irene and
Garc{\'\i}a-Garc{\'e}s, Luis and
del-Hoyo-Alonso, Rafael",
editor = "Gonzalez-Hernandez, Graciela and
Weissenbacher, Davy",
booktitle = "Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop {\&} Shared Task",
month = oct,
year = "2022",
address = "Gyeongju, Republic of Korea",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.smm4h-1.21",
pages = "71--74",
abstract = "ITAINNOVA participates in SocialDisNER with a hybrid system which combines Transformer-based Language Models (LMs) with a custom-built gazetteer for Approximate String Matching (ASM) and dedicated text processing techniques for the social media domain. Additionally, zero-shot classification capabilities have been explored in order to support different parts of the system. An extensive analysis on the interactions of these components has been accomplished, making the system stand out above the mean performance of all the participating teams.",
}
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%0 Conference Proceedings
%T ITAINNOVA at SocialDisNER: A Transformers cocktail for disease identification in social media in Spanish
%A Montañés-Salas, Rosa
%A López-Bosque, Irene
%A García-Garcés, Luis
%A del-Hoyo-Alonso, Rafael
%Y Gonzalez-Hernandez, Graciela
%Y Weissenbacher, Davy
%S Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop & Shared Task
%D 2022
%8 October
%I Association for Computational Linguistics
%C Gyeongju, Republic of Korea
%F montanes-salas-etal-2022-itainnova
%X ITAINNOVA participates in SocialDisNER with a hybrid system which combines Transformer-based Language Models (LMs) with a custom-built gazetteer for Approximate String Matching (ASM) and dedicated text processing techniques for the social media domain. Additionally, zero-shot classification capabilities have been explored in order to support different parts of the system. An extensive analysis on the interactions of these components has been accomplished, making the system stand out above the mean performance of all the participating teams.
%U https://aclanthology.org/2022.smm4h-1.21
%P 71-74
Markdown (Informal)
[ITAINNOVA at SocialDisNER: A Transformers cocktail for disease identification in social media in Spanish](https://aclanthology.org/2022.smm4h-1.21) (Montañés-Salas et al., SMM4H 2022)
ACL