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In this paper, we present 'EXABSUM,' a novel approach to Automatic Text Summarization (ATS), capable of generating the two primary types of summaries: extractive and abstractive. We propose two distinct approaches: (1) an extractive technique (EXABSUM<jats:sub>Extractive<\/jats:sub>), which integrates statistical and semantic scoring methods to select and extract relevant, non-repetitive sentences from a text unit, and (2) an abstractive technique (EXABSUM<jats:sub>Abstractive<\/jats:sub>), which employs a word graph approach (including compression and fusion stages) and re-ranking based on keyphrases to generate abstractive summaries using the source document as an input. In the evaluation conducted on multi-domain benchmarks, EXABSUM outperformed extractive summarization methods and demonstrated competitiveness against abstractive baselines.<\/jats:p>","DOI":"10.1186\/s40537-023-00836-y","type":"journal-article","created":{"date-parts":[[2023,10,24]],"date-time":"2023-10-24T11:02:30Z","timestamp":1698145350000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":34,"title":["EXABSUM: a new text summarization approach for generating extractive and abstractive summaries"],"prefix":"10.1186","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0903-6160","authenticated-orcid":false,"given":"Zakariae","family":"Alami Merrouni","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bouchra","family":"Frikh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brahim","family":"Ouhbi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,10,24]]},"reference":[{"key":"836_CR1","unstructured":"Hovy E, Marcu D. 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