论文标题
COVIDSCHOLAL：自动化的COVID-19研究聚合和分析平台
COVIDScholar: An automated COVID-19 research aggregation and analysis platform
论文作者
论文摘要
持续的共同19-19大流行在整个社会中都具有深远的影响，科学也不例外。科学界的COVID-19反应的规模，速度和广度导致了新的研究文献的出现 - 截至2020年10月，已经发布了超过250次超过250个相关的科学论文。这给传统的与研究文献的互动构成了挑战。新研究的数量远远超出了任何人类阅读的能力，而紧迫性的紧迫性导致了预印刷服务器的越来越重要的作用，并且跨来源的相关研究的扩散。这些因素创造了需要新工具来改变科学文献传播方式的新工具。 Covidscholar是一个知识门户，旨在考虑到Covid-19研究社区的独特需求，利用NLP来帮助研究人员综合跨成千上万种新兴的研究文章，专利和临床试验的信息，以融合到可行的见解和新知识中。该语料库的搜索接口https://covidscholar.org现在每周为2000多个唯一用户服务。我们还介绍了2020年Covid-19研究趋势的分析。
The ongoing COVID-19 pandemic has had far-reaching effects throughout society, and science is no exception. The scale, speed, and breadth of the scientific community's COVID-19 response has lead to the emergence of new research literature on a remarkable scale -- as of October 2020, over 81,000 COVID-19 related scientific papers have been released, at a rate of over 250 per day. This has created a challenge to traditional methods of engagement with the research literature; the volume of new research is far beyond the ability of any human to read, and the urgency of response has lead to an increasingly prominent role for pre-print servers and a diffusion of relevant research across sources. These factors have created a need for new tools to change the way scientific literature is disseminated. COVIDScholar is a knowledge portal designed with the unique needs of the COVID-19 research community in mind, utilizing NLP to aid researchers in synthesizing the information spread across thousands of emergent research articles, patents, and clinical trials into actionable insights and new knowledge. The search interface for this corpus, https://covidscholar.org, now serves over 2000 unique users weekly. We present also an analysis of trends in COVID-19 research over the course of 2020.
