Collecting Targeted Information about COVID-19 from Research Papers by Asking Questions Based On Natural Language Processing
May 08

Collecting Targeted Information about COVID-19 from Research Papers by Asking Questions Based On Natural Language Processing

As the COVID-19 is now and again surging in many countries around the world and with new variants, it has become a global priority for research to obtain deep information that can easily combat Coronavirus. There is so much up-to-date COVID-19 related information available from scholarly journals. This pool of information poses challenges for the public and other researchers to easily spot and extract the information and insights they need it.

A group of researchers almost from SIMAD University developed a sophisticated model that provides relevant information by giving appropriate and much accurate answers of what users requested or asked by retrieving from the body of different articles.  The system allows researchers and the public an easier extraction of valuable information about COVID-19 from multiple scholarly articles using Natural Language Processing.

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