@inproceedings{leaman-lu-2020-comprehensive,
title = "A Comprehensive Dictionary and Term Variation Analysis for {COVID}-19 and {SARS}-{C}o{V}-2",
author = "Leaman, Robert and
Lu, Zhiyong",
editor = "Verspoor, Karin and
Cohen, Kevin Bretonnel and
Conway, Michael and
de Bruijn, Berry and
Dredze, Mark and
Mihalcea, Rada and
Wallace, Byron",
booktitle = "Proceedings of the 1st Workshop on {NLP} for {COVID}-19 (Part 2) at {EMNLP} 2020",
month = dec,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.nlpcovid19-2.32",
doi = "10.18653/v1/2020.nlpcovid19-2.32",
abstract = "The number of unique terms in the scientific literature used to refer to either SARS-CoV-2 or COVID-19 is remarkably large and has continued to increase rapidly despite well-established standardized terms. This high degree of term variation makes high recall identification of these important entities difficult. In this manuscript we present an extensive dictionary of terms used in the literature to refer to SARS-CoV-2 and COVID-19. We use a rule-based approach to iteratively generate new term variants, then locate these variants in a large text corpus. We compare our dictionary to an extensive collection of terminological resources, demonstrating that our resource provides a substantial number of additional terms. We use our dictionary to analyze the usage of SARS-CoV-2 and COVID-19 terms over time and show that the number of unique terms continues to grow rapidly. Our dictionary is freely available at \url{https://github.com/ncbi-nlp/CovidTermVar}.",
}
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%0 Conference Proceedings
%T A Comprehensive Dictionary and Term Variation Analysis for COVID-19 and SARS-CoV-2
%A Leaman, Robert
%A Lu, Zhiyong
%Y Verspoor, Karin
%Y Cohen, Kevin Bretonnel
%Y Conway, Michael
%Y de Bruijn, Berry
%Y Dredze, Mark
%Y Mihalcea, Rada
%Y Wallace, Byron
%S Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020
%D 2020
%8 December
%I Association for Computational Linguistics
%C Online
%F leaman-lu-2020-comprehensive
%X The number of unique terms in the scientific literature used to refer to either SARS-CoV-2 or COVID-19 is remarkably large and has continued to increase rapidly despite well-established standardized terms. This high degree of term variation makes high recall identification of these important entities difficult. In this manuscript we present an extensive dictionary of terms used in the literature to refer to SARS-CoV-2 and COVID-19. We use a rule-based approach to iteratively generate new term variants, then locate these variants in a large text corpus. We compare our dictionary to an extensive collection of terminological resources, demonstrating that our resource provides a substantial number of additional terms. We use our dictionary to analyze the usage of SARS-CoV-2 and COVID-19 terms over time and show that the number of unique terms continues to grow rapidly. Our dictionary is freely available at https://github.com/ncbi-nlp/CovidTermVar.
%R 10.18653/v1/2020.nlpcovid19-2.32
%U https://aclanthology.org/2020.nlpcovid19-2.32
%U https://doi.org/10.18653/v1/2020.nlpcovid19-2.32
Markdown (Informal)
[A Comprehensive Dictionary and Term Variation Analysis for COVID-19 and SARS-CoV-2](https://aclanthology.org/2020.nlpcovid19-2.32) (Leaman & Lu, NLP-COVID19 2020)
ACL