论文标题
从大量的科学论文中获取有关专业综合主题的见解 - Covid-19
Getting Insights from a Large Corpus of Scientific Papers on Specialisted Comprehensive Topics -- the Case of COVID-19
论文作者
论文摘要
Covid-19是当今最重要的话题之一，特别是在搜索引擎和新闻方面。尽管很容易共享假新闻，但科学论文是可以提取信息的可靠来源。借助大约24,000个有关Covid-19的科学出版物和有关PubMed的相关研究，需要自动计算机辅助分析。在本文中，我们开发了两种方法，以了解有关感兴趣的特定子主题和最新研究子主题的见解。他们依靠自然语言处理和基于图的可视化。我们在两种情况下运行这些方法：病毒起源和现有药物的用途。
COVID-19 is one of the most important topic these days, specifically on search engines and news. While fake news are easily shared, scientific papers are reliable sources where information can be extracted. With about 24,000 scientific publications on COVID-19 and related research on PUBMED, automatic computer-assisted analysis is required. In this paper, we develop two methodologies to get insights on specific sub-topics of interest and latest research sub-topics. They rely on natural language processing and graph-based visualizations. We run these methodologies on two cases: the virus origin and the uses of existing drugs.
