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Thomas Ashton Institute for Risk and Regulatory Research

COVID-19 search system demonstrated by Professor Sophia Ananiadou, Director of the National Centre for Text Mining

10 June 2021

The COVID-19 pandemic resulted in an unprecedented production of scientific literature spanning several fields. While the primary focus was undeniably the biomedical domain (from virology to vaccines and therapeutics), there were multiple other domains affected, such as socioeconomic studies, public health, environment, etc.

Alongside scientists, a broad group of other practitioners consult the continuously changing literature in order to make informed decisions about patient care, social and work policies and guidelines. To support their scientific discovery, our contribution is the development of a term, entity and citation-based search system based on the CORD-19 Open Research Dataset.  

The search system aims to facilitate navigation of the scientific literature related to various aspects of the coronavirus pandemic.

Image of virus with web browser search box

The system is based on automatically recognised terms, their visualisation, entities and timelines to accelerate identification of relevant documents. It offers a multi-view interactive search and navigation interface, bringing together unsupervised approaches of term extraction, entity recognition, and citation analysis.

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