论文标题
COVIDEXPLORER：用于COVID-19信息的多面AI基于AI的搜索和可视化引擎
CovidExplorer: A Multi-faceted AI-based Search and Visualization Engine for COVID-19 Information
论文作者
论文摘要
全世界都陷入了与19日大流行的斗争中，导致研究实验，政府政策和社交媒体讨论的巨大激增。多模式信息访问和数据可视化平台在支持旨在理解和制定大流行预防措施的研究中起着关键作用。在本文中，我们提出了一个基于AI的多方面搜索和可视化引擎Covidexplorer。我们的系统旨在帮助研究人员了解当前的最新COVID-19研究，确定与其领域相关的研究文章，以及可视化COVID-19病例的实时趋势和统计数据。与其他现有系统相反，Covidexplorer还在社交媒体上引发了印度特定的主题讨论，以研究Covid-19的不同方面。系统，演示视频和数据集可在http://covidexplorer.in上找到。
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.
