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TREC-COVID: Rationale and Structure of an Information Retrieval Shared Task for COVID-19
Published
Author(s)
Ellen Voorhees, Ian Soboroff, Tasmeer Alam, Kirk Roberts, William Hersh, Dina Demner-Fushman, Steven Bedrick, Kyle Lo, Lucy L. Wang
Abstract
TREC-COVID is an information retrieval (IR) shared task initiated to support clinicians and clinical research during the COVID-19 pandemic. IR for pandemics breaks many normal assumptions, which can be seen by examining nine important basic IR research questions related to pandemic situations. TREC-COVID differs from traditional IR shared task evaluations with special considerations for the expected users, IR modality considerations, topic development, participant requirements, assessment process, relevance criteria, evaluation metrics, iteration process, projected timeline, and the implications of data use as a post-task test collection. We describe how all these were addressed for the particular requirements of developing IR systems under a pandemic situation. Finally, initial participation numbers are also provided, which demonstrate the tremendous interest the IR community has in this effort.
Citation
Journal of the American Medical Informatics Association
Voorhees, E.
, Soboroff, I.
, Alam, T.
, Roberts, K.
, Hersh, W.
, Demner-Fushman, D.
, Bedrick, S.
, Lo, K.
and Wang, L.
(2020),
TREC-COVID: Rationale and Structure of an Information Retrieval Shared Task for COVID-19, Journal of the American Medical Informatics Association, [online], https://doi.org/10.1093/jamia/ocaa091, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=930305
(Accessed October 10, 2025)