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Collecting Targeted Information About Covid-19 From Research Papers By Asking Questions Based On Natural Language Processing

Collecting Targeted Information About Covid-19 From Research Papers By Asking Questions Based On Natural Language Processing
	© 2021 by IJETT Journal
	Volume-69 Issue-5
	Year of Publication : 2021
	Authors : Abdirahman Osman Hashi, Octavio Ernesto Romo Rodriguez, Abdullahi Ahmed Abdirahman, Mohamed M. Mohamed
	DOI :  10.14445/22315381/IJETT-V69I5P226

How to Cite?

Abdirahman Osman Hashi, Octavio Ernesto Romo Rodriguez, Abdullahi Ahmed Abdirahman, Mohamed M. Mohamed, "Collecting Targeted Information About Covid-19 From Research Papers By Asking Questions Based On Natural Language Processing," International Journal of Engineering Trends and Technology, vol. 69, no. 5, pp. 190-195, 2021. Crossref, https://doi.org/10.14445/22315381/IJETT-V69I5P226

Abstract
In the general framework of knowledge discovery, different techniques were used for information extraction from multi-label documents. As the world is currently facing COVID-19, it has made it more important than ever to have such knowledge extraction from previous documents. Therefore, Natural Language Processing (NLP) can be an essential model for tackling such an issue. By taking into consideration that having such a model plays an essential role to generate new insights in support of the ongoing fight against this infectious disease. This work introduces a sophisticated model that is able to read data from various articles about COVID-19, and finally give the most appropriate answer to the questions asked in order to gain insight information automatically. The model is applied to COVID-19 open research dataset challenge (CORD-19) that’s has caught the attention of many researchers and it contains over 400,000 scholarly articles. The result of the proposed model has shown a good achievement, as it is explained in the result section. It was found that NLP is a good choice for tackling this global pandemic for information extraction and it contribute a new insight in support of the ongoing fight against this infectious disease.

Keywords
Coronavirus; Natural Language Processing; Deep Learning, Artificial Intelligence.

Reference
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