Automatic Text Summarization of COVID-19 Scientific Research Topics Using Pre-trained Models from Hugging Face

Abstract

Automated text summarizing helps the scientific and medical sectors by identifying and extracting relevant information from articles. Automatic text summarization is a way of compressing text documents so that users may find important and useful information in the original text in reduced time. We will first review some new works in the field of summarization that uses deep learning approaches, and then we will explain the application to COVID-19 related research papers. The ease with which a reader can grasp written text is referred to as the readability test. The substance of text determines its readability in natural language processing. We constructed word clouds using the abstracts’ most commonly used text. By looking at those three measurements, we can determine the performance measures of ROUGE-1, ROUGE-2, ROUGE-L, ROUGE-L-SUM. Our findings indicated that Distilbart-mnli-12-6 and GPT2-large outperform than others considered.