A Self-supervised Approach for Semantic Indexing in the Context of COVID-19 Pandemic
Nima Ebadi,
Peyman Najafirad
Abstract:The pandemic has accelerated the pace at which COVID-19 scientific papers are published. In addition, the process of manually assigning semantic indexes to these papers by experts is even more time-consuming and overwhelming in the current health crisis. Therefore, there is an urgent need for automatic semantic indexing models which can effectively scale-up to newly introduced concepts and rapidly evolving distributions of the hyperfocused related literature. In this research, we present a novel semantic index… Show more
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