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Sakdipat_CORD_19_Text_Sum_61130500229_report_v1.pdf (1015.43 kB)
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Automatic Text Summaration of COVID-19 Scientific Research Topics Using Pre-trained Model from HuggingFace®

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By identifying and extracting relevant information from articles, automated text summarizing helps the scientific and medical sectors. Automatic text summarization is a way of compressing text documents so that users may find important information in the original text in less time. We will first review some new works in the field of summarizing that use deep learning approaches, and then we will explain the "COVID-19" summarization 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 abstract's most commonly used text. By looking at those three measurements, we can determine the mean of "ROUGE-1", "ROUGE-2", and "ROUGE-L". As a consequence, "Distilbart-mnli-12-6" and "GPT2-large" are outperform than other.

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Email Address of Submitting Author

sakdipat.2542@mail.kmutt.ac.th

ORCID of Submitting Author

https://orcid.org/0000-0001-5316-0401

Submitting Author's Institution

King Mongkut’s University of Technology Thonburi

Submitting Author's Country

Thailand

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