Searching for scientific evidence in a pandemic: An overview of TREC-COVID

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

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

We present an overview of the TREC-COVID Challenge, an information retrieval (IR) shared task to evaluate search on scientific literature related to COVID-19. The goals of TREC-COVID include the construction of a pandemic search test collection and the evaluation of IR methods for COVID-19. The challenge was conducted over five rounds from April to July 2020, with participation from 92 unique teams and 556 individual submissions. A total of 50 topics (sets of related queries) were used in the evaluation, starting at 30 topics for Round 1 and adding 5 new topics per round to target emerging topics at that state of the still-emerging pandemic. This paper provides a comprehensive overview of the structure and results of TREC-COVID. Specifically, the paper provides details on the background, task structure, topic structure, corpus, participation, pooling, assessment, judgments, results, top-performing systems, lessons learned, and benchmark datasets.

Original languageEnglish (US)
Article number103865
JournalJournal of Biomedical Informatics
Volume121
DOIs
StatePublished - Sep 2021

Keywords

  • COVID-19
  • Information retrieval
  • Pandemics
  • TREC-COVID

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics

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