Back to Search Start Over

CovidExplorer: A Multi-faceted AI-based Search and Visualization Engine for COVID-19 Information

Authors :
Ambavi, Heer
Vaishnaw, Kavita
Vyas, Udit
Tiwari, Abhisht
Singh, Mayank
Publication Year :
2020

Abstract

The entire world is engulfed in the fight against the COVID-19 pandemic, leading to a significant surge in research experiments, government policies, and social media discussions. A multi-modal information access and data visualization platform can play a critical role in supporting research aimed at understanding and developing preventive measures for the pandemic. In this paper, we present a multi-faceted AI-based search and visualization engine, CovidExplorer. Our system aims to help researchers understand current state-of-the-art COVID-19 research, identify research articles relevant to their domain, and visualize real-time trends and statistics of COVID-19 cases. In contrast to other existing systems, CovidExplorer also brings in India-specific topical discussions on social media to study different aspects of COVID-19. The system, demo video, and the datasets are available at http://covidexplorer.in.<br />Comment: 4 pages, 7 figures, The associated system can be accessed at http://covidexplorer.in, To be published in the Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM '20) (October 19-23, 2020)(Virtual Event, Ireland)

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2011.14618
Document Type :
Working Paper
Full Text :
https://doi.org/10.1145/3340531.3417428