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In this regard, the exponential growth of COVID\u201019\u2010related healthcare records has necessitated the extraction of fine\u2010grained results to forecast or estimate the potential course of the disease. Machine learning and deep learning models are frequently used to extract relevant insights from textual data sources. However, in order to summarize the textual information relevant to coronavirus, we have concentrated on a number of natural language processing (NLP) models in this research, including Bidirectional Encoder Representations of Transformers (BERT), Sequence\u2010to\u2010Sequence, and Attention models. This ensemble model is built on the previously mentioned models, which primarily concentrate on the segmented context terms included in the textual input. Most crucially, this research has concentrated on two key variations: grouping\u2010related sentences using hierarchical clustering approaches and the distributional semantics of the terms found in the COVID\u201019 dataset. The gist evaluation (ROUGE) score result shows a significant and respectable accuracy of 0.40 average recalls.<\/jats:p>","DOI":"10.1155\/2023\/3106631","type":"journal-article","created":{"date-parts":[[2023,12,11]],"date-time":"2023-12-11T18:13:02Z","timestamp":1702318382000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Ensemble Text Summarization Model for COVID\u201019\u2010Associated Datasets"],"prefix":"10.1155","volume":"2023","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8225-0588","authenticated-orcid":false,"given":"T.","family":"Chellatamilan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2951-5740","authenticated-orcid":false,"given":"Senthil Kumar","family":"Narayanasamy","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3868-0481","authenticated-orcid":false,"given":"Lalit","family":"Garg","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9352-0237","authenticated-orcid":false,"given":"Kathiravan","family":"Srinivasan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9451-7390","authenticated-orcid":false,"given":"Sardar M. 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