Artículo
A term-based and citation network-based search system for COVID-19
Fecha de publicación:
10/2021
Editorial:
Oxford University Press
Revista:
JAMIA Open
ISSN:
2574-2531
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
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/.
Palabras clave:
COVID-19
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Colecciones
Articulos (ICIC)
Articulos de INSTITUTO DE CS. E INGENIERIA DE LA COMPUTACION
Articulos de INSTITUTO DE CS. E INGENIERIA DE LA COMPUTACION
Citación
Zerva, Chrysoula; Taylor, Samuel; Soto, Axel Juan; Nguyen, Nhung T. H.; Ananiadou, Sophia; A term-based and citation network-based search system for COVID-19; Oxford University Press; JAMIA Open; 4; 4; 10-2021; 1-7
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