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PUBLICATIONS

TREC-COVID: Constructing a Pandemic Information Retrieval Test Collection

Published

Author(s)

Ellen Voorhees, Ian Soboroff, Tasmeer Alam, William Hersh, Kirk Roberts, Dina Demner-Fushman, Kyle Lo, Lucy L. Wang, Steven Bedrick

Abstract

TREC-COVID is a community evaluation designed to build a test collection that captures the information needs of biomedical researchers using the scientific literature during a pandemic. One of the key characteristics of pandemic search is the accelerated rate of change: the topics of interest evolve as the pandemic progresses and the scientific literature in the area explodes. The COVID-19 pandemic provides an opportunity to capture this progression as it happens. TREC-COVID, in creating a test collection around COVID-19 literature, is building infrastructure to support new research and technologies in pandemic search.
Citation
ACM SIGIR Forum
Volume
54
Issue
1
Pub Type
Others

Download Paper

https://doi.org/10.1145/3451964.3451965
Local Download

Keywords

information retrieval, test collections, TREC
Information retrieval, Data and informatics and Artificial intelligence

Citation

Voorhees, E. , Soboroff, I. , Alam, T. , Hersh, W. , Roberts, K. , Demner-Fushman, D. , Lo, K. , Wang, L. and Bedrick, S. (2021), TREC-COVID: Constructing a Pandemic Information Retrieval Test Collection, ACM SIGIR Forum, [online], https://doi.org/10.1145/3451964.3451965, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=930360 (Accessed October 9, 2025)

Issues

If you have any questions about this publication or are having problems accessing it, please contact [email protected].

Created February 19, 2021, Updated September 29, 2025
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