AWS CORD19-Search: A Scientific Literature Search Engine for COVID-19
Year: 2020
Type: preprint
Abstract: Coronavirus disease (COVID-19) has been declared as a pandemic by WHO with thousands of cases being reported each day. Thousands of scientific articles are being published on the disease raising the need for a service which can organize, and query them in a reliable fashion. To support this cause, we present AWS CORD-19 Search (ACS), a public COVID-19 specific search engine that is powered by machine learning. ACS with its capabilities such as topic based, natural language search queries, and reading comprehension and FAQ matching provides a scalable solution to COVID-19 researchers and policy makers in their search and discovery for answers to high priority scientific questions. We present evaluation and qualitative analysis of the system with specific examples to illustrate the capabilities of the system.
Source: arXiv (Cornell University)
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3043141663