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Author Spotlight: Advancements in Multiplex Detection of Respiratory Viruses
Published on: November 10, 2023
A term-based and citation network-based search system for COVID-19
Chrysoula Zerva1,2, Samuel Taylor1, Axel J Soto3
1Department of Computer Science, National Centre for Text Mining, Manchester Interdisciplinary Biocentre, The University of Manchester, Manchester, UK.
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 visualization, 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 visualization and filters. The system is updated on a weekly basis and it is publicly available at http://www.nactem.ac.uk/cord/.
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