CovidExplorer: A Multi-faceted AI-based Search and Visualization Engine for COVID-19 Information
November 30, 2020 Β· Declared Dead Β· π International Conference on Information and Knowledge Management
"No code URL or promise found in abstract"
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Authors
Heer Ambavi, Kavita Vaishnaw, Udit Vyas, Abhisht Tiwari, Mayank Singh
arXiv ID
2011.14618
Category
cs.IR: Information Retrieval
Cross-listed
cs.CL,
cs.SI
Citations
5
Venue
International Conference on Information and Knowledge Management
Last Checked
4 months ago
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.
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