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Searching for Scientific Evidence in a Pandemic: An Overview of TREC-COVID (2104.09632v1)

Published 19 Apr 2021 in cs.IR

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.

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Authors (9)
  1. Kirk Roberts (32 papers)
  2. Tasmeer Alam (2 papers)
  3. Steven Bedrick (7 papers)
  4. Dina Demner-Fushman (22 papers)
  5. Kyle Lo (73 papers)
  6. Ian Soboroff (13 papers)
  7. Ellen Voorhees (2 papers)
  8. Lucy Lu Wang (41 papers)
  9. William R Hersh (2 papers)
Citations (23)

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