A Term-based and Citation Network-based Search System for COVID-19

Chrysoula Zerva, Samuel Taylor, Axel Soto, Nhung Nguyen, Sophia Ananiadou

Research output: Contribution to journalArticlepeer-review

Abstract

The COVID-19 pandemic resulted in an unprecedented production of scientific literature spanning several fields. To facilitate navigation of the scientific literature related to various aspects of the pandemic, we developed an exploratory search system. The system is based on automatically identified technical terms, document citations and their visualisation, accelerating identification of relevant documents. It offers a multi-view interactive search and navigation interface, bringing together unsupervised approaches of term extraction and citation analysis. We conducted a user evaluation with domain experts, including epidemiologists, biochemists, medicinal chemists, and medicine students. In general, most users were satisfied with the relevance and speed of the search results. More interestingly, participants mostly agreed on the capacity of the system to enable exploration and discovery of the search space using the graph visualisation and filters. The system is updated on a weekly basis and it is publicly available at http://www.nactem.ac.uk/cord/.
Original languageEnglish
JournalJAMIA Open
Publication statusAccepted/In press - 18 Nov 2021

Research Beacons, Institutes and Platforms

  • Thomas Ashton Institute

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