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A term-based and citation network-based search system for COVID-19.
Zerva, Chrysoula; Taylor, Samuel; Soto, Axel J; Nguyen, Nhung T H; Ananiadou, Sophia.
  • Zerva C; Department of Computer Science, National Centre for Text Mining, Manchester Interdisciplinary Biocentre, The University of Manchester, Manchester, UK.
  • Taylor S; Chrysoula Zerva's affiliation at the time of submission/publicationis is Instituto de Telecomunicações (IT), Lisbon, Portugal. All work was carried out while the author was employed at the University of Manchester, UK.
  • Soto AJ; Department of Computer Science, National Centre for Text Mining, Manchester Interdisciplinary Biocentre, The University of Manchester, Manchester, UK.
  • Nguyen NTH; Department of Computer Science and Engineering, Universidad Nacional del Sur & Institute for Computer Science and Engineering (ICIC, UNS-CONICET), Bahia Blanca, Argentina.
  • Ananiadou S; Department of Computer Science, National Centre for Text Mining, Manchester Interdisciplinary Biocentre, The University of Manchester, Manchester, UK.
JAMIA Open ; 4(4): ooab104, 2021 Oct.
Article in English | MEDLINE | ID: covidwho-2070142
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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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies Language: English Journal: JAMIA Open Year: 2021 Document Type: Article Affiliation country: Jamiaopen

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies Language: English Journal: JAMIA Open Year: 2021 Document Type: Article Affiliation country: Jamiaopen