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• W3092619036 abstract "Coronavirus disease (COVID-19) has been declared as a pandemic by WHO with thousands of cases being reported each day. Numerous 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, neural search engine that is powered by several machine learning systems to support natural language based searches. ACS with capabilities such as document ranking, passage ranking, question answering, knowledge graph based ranking and biomedical topic classification 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 a quantitative evaluation and qualitative analysis of the system against other leading COVID-19 search platforms. ACS is top performing across these systems yielding quality results which we detail with relevant examples in this work." @default.
• W3092619036 created "2020-10-15" @default.
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• W3092619036 date "2022-01-01" @default.
• W3092619036 modified "2023-10-18" @default.
• W3092619036 title "AWS CORD-19 Search: A Neural Search Engine for COVID-19 Literature" @default.
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• W3092619036 doi "https://doi.org/10.1007/978-3-030-93080-6_11" @default.
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