z-logo
open-access-imgOpen Access
TREC-COVID: rationale and structure of an information retrieval shared task for COVID-19
Author(s) -
Kirk Roberts,
Tasmeer Alam,
Steven Bedrick,
Dina DemnerFushman,
Kyle Lo,
Ian Soboroff,
Ellen M. Voorhees,
Lucy Lu Wang,
William Hersh
Publication year - 2020
Publication title -
journal of the american medical informatics association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.614
H-Index - 150
eISSN - 1527-974X
pISSN - 1067-5027
DOI - 10.1093/jamia/ocaa091
Subject(s) - covid-19 , task (project management) , computer science , information retrieval , betacoronavirus , medline , virology , medicine , biology , pathology , disease , management , infectious disease (medical specialty) , economics , biochemistry , outbreak
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 9 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. This article describes 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.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom