A Comparative Study of Clustering Techniques Applied on Covid-19 Scientific Literature

Abstract

Due to the current emergency situation, caused by COVID-19, the scientific literature on the topic has rapidly grown. At the same time, purposeful and targeted research plans with strong background knowledge is urgently needed. However, the huge number of documents produced by multiple communities generates a fragmented terminology that may cause confusion in information retrieval. To this aim, in a comparative study, we test different techniques to efficiently cluster these publications for improving their level of findability.