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.
@article{arxiv.2011.14618,
title = {CovidExplorer: A Multi-faceted AI-based Search and Visualization Engine for COVID-19 Information},
author = {Heer Ambavi and Kavita Vaishnaw and Udit Vyas and Abhisht Tiwari and Mayank Singh},
journal= {arXiv preprint arXiv:2011.14618},
year = {2020}
}
Comments
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)