COVIDSeer : Filling missing pieces in the CORD-19 dataset

We develop an enhanced version of CORD19 dataset released by the Allen Institute for AI. Our tools in our SeerSuite project are used to exploit information in original articles but not directly provided in the CORD-19 datasets. We add 728 new abstracts, 70,102 figures and 31,446 tables with captions that are not provided in the current data release. We also built a vertical search engine COVIDSeer based on the new dataset we created. COVIDSeer is a relatively simple architecture with features like keyword filtering, and similar paper recommendation. The goal was to provide a system and dataset that can help scientists better navigate through the literature around COVID19. The enriched dataset serves as a supplement to the existing dataset. The search engine, which offers keyphrase-enhanced search, will hopefully help biomedical and life science researchers, medical students, and the general public to explore coronavirus-related literature more effectively. The entire data set and system will be made open source.

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