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CORA: A Deep Active Learning Covid-19 Relevancy Algorithm to Identify Core Scientific Articles
Ever since the COVID-19 pandemic broke out, the academic and scientific research community, as well as industry and governments around the world have joined forces in an unprecedented manner to fight the threat.
Tagging Funding Agencies and Grants in Scientific Articles using Sequential Learning Models
In this paper we present a solution for tagging funding bodies and grants in scientific articles using a combination of trained sequential learning models, namely conditional random fields (CRF), hidden markov models (HMM) and maximum entropy models (MaxEnt), on a benchmark set created in-house.
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