The world has faced the devastating outbreak of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), or COVID-19, in 2020. Research in the subject matter was fast-tracked to such a point that scientists were struggling to keep up with new findings. With this increase in the scientific literature, there arose a need for organizing those documents. We describe an approach to organize and visualize the scientific literature on or related to COVID-19 using machine learning techniques so that papers on similar topics are grouped together. By doing so, the navigation of topics and related papers is simplified. We implemented this approach using the widely recognized CORD-19 dataset to present a publicly available proof of concept.

中文翻译：

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COVID-19 Kaggle 文学组织

2020 年，世界面临严重急性呼吸系统综合症冠状病毒 2 (SARS-CoV-2) 或 COVID-19 的毁灭性爆发。该主题的研究进展迅速，以至于科学家们都在努力保持跟上新的发现。随着科学文献的增加，需要组织这些文件。我们描述了一种使用机器学习技术组织和可视化关于 COVID-19 或与 COVID-19 相关的科学文献的方法，以便将类似主题的论文分组在一起。通过这样做，可以简化主题和相关论文的导航。我们使用广泛认可的 CORD-19 数据集实现了这种方法，以提供公开可用的概念证明。