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

arXiv: https://arxiv.org/abs/2011.14618 · HTML: https://mlsanity.com/paper/2011.14618/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Nov 2020.

## Built on by (most cited first, 1 of 1)

- [Large-Scale Knowledge Synthesis and Complex Information Retrieval from Biomedical Documents](https://mlsanity.com/paper/2302.06854/) (2023)

## Abstract (arXiv)

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.