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A term-based and citation network-based search system for COVID-19
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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8672931/ https://www.ncbi.nlm.nih.gov/pubmed/34927002 http://dx.doi.org/10.1093/jamiaopen/ooab104 |
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author | Zerva, Chrysoula Taylor, Samuel Soto, Axel J Nguyen, Nhung T H Ananiadou, Sophia |
author_facet | Zerva, Chrysoula Taylor, Samuel Soto, Axel J Nguyen, Nhung T H Ananiadou, Sophia |
author_sort | Zerva, Chrysoula |
collection | PubMed |
description | 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/. |
format | Online Article Text |
id | pubmed-8672931 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-86729312021-12-16 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 JAMIA Open Application Notes 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/. Oxford University Press 2021-12-14 /pmc/articles/PMC8672931/ /pubmed/34927002 http://dx.doi.org/10.1093/jamiaopen/ooab104 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Application Notes Zerva, Chrysoula Taylor, Samuel Soto, Axel J Nguyen, Nhung T H Ananiadou, Sophia A term-based and citation network-based search system for COVID-19 |
title | A term-based and citation network-based search system for
COVID-19 |
title_full | A term-based and citation network-based search system for
COVID-19 |
title_fullStr | A term-based and citation network-based search system for
COVID-19 |
title_full_unstemmed | A term-based and citation network-based search system for
COVID-19 |
title_short | A term-based and citation network-based search system for
COVID-19 |
title_sort | term-based and citation network-based search system for
covid-19 |
topic | Application Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8672931/ https://www.ncbi.nlm.nih.gov/pubmed/34927002 http://dx.doi.org/10.1093/jamiaopen/ooab104 |
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