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Text summarisation for low-resourced languages: A review

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dc.contributor.author Edwards, Gareth R
dc.contributor.author Sefara, Tshephisho J
dc.date.accessioned 2024-06-11T08:50:22Z
dc.date.available 2024-06-11T08:50:22Z
dc.date.issued 2024-04
dc.identifier.citation Edwards, G.R. & Sefara, T.J. 2024. Text summarisation for low-resourced languages: A review. http://hdl.handle.net/10204/13690 . en_ZA
dc.identifier.isbn 978-3-031-58494-7
dc.identifier.isbn 978-3-031-58495-4
dc.identifier.uri https://doi.org/10.1007/978-3-031-58495-4_21
dc.identifier.uri http://hdl.handle.net/10204/13690
dc.description.abstract Text summarisation is becoming increasingly important for humans to more quickly understand and analyse documents with large amounts of text. In this paper, we review and discuss approaches and methods used in the development of text summarisation models for low-resourced languages, specifically South African languages. We compare approaches and results to give guidance on what may be the best approach to building a sophisticated text summarisation model for South African languages. The results showed that there is one text summarisation model created for isiXhosa out of 11 South African languages, and only a few studies were done for African languages. en_US
dc.format Fulltext en_US
dc.language.iso en en_US
dc.relation.uri https://link.springer.com/chapter/10.1007/978-3-031-58495-4_21 en_US
dc.relation.uri https://link.springer.com/book/10.1007/978-3-031-58495-4 en_US
dc.source Second International Conference, SPELLL 2023, Erode, India, 6-8 December 2023 en_US
dc.subject Text summarisation en_US
dc.subject Low-resource languages en_US
dc.subject Natural Language Processing en_US
dc.title Text summarisation for low-resourced languages: A review en_US
dc.type Conference Presentation en_US
dc.description.pages 283–296 en_US
dc.description.note This is the preprint version of the work. en_US
dc.description.cluster Next Generation Enterprises & Institutions en_US
dc.description.impactarea Data Science en_US
dc.identifier.apacitation Edwards, G. R., & Sefara, T. J. (2024). Text summarisation for low-resourced languages: A review. http://hdl.handle.net/10204/13690 en_ZA
dc.identifier.chicagocitation Edwards, Gareth R, and Tshephisho J Sefara. "Text summarisation for low-resourced languages: A review." <i>Second International Conference, SPELLL 2023, Erode, India, 6-8 December 2023</i> (2024): http://hdl.handle.net/10204/13690 en_ZA
dc.identifier.vancouvercitation Edwards GR, Sefara TJ, Text summarisation for low-resourced languages: A review; 2024. http://hdl.handle.net/10204/13690 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Edwards, Gareth R AU - Sefara, Tshephisho J AB - Text summarisation is becoming increasingly important for humans to more quickly understand and analyse documents with large amounts of text. In this paper, we review and discuss approaches and methods used in the development of text summarisation models for low-resourced languages, specifically South African languages. We compare approaches and results to give guidance on what may be the best approach to building a sophisticated text summarisation model for South African languages. The results showed that there is one text summarisation model created for isiXhosa out of 11 South African languages, and only a few studies were done for African languages. DA - 2024-04 DB - ResearchSpace DP - CSIR J1 - Second International Conference, SPELLL 2023, Erode, India, 6-8 December 2023 KW - Text summarisation KW - Low-resource languages KW - Natural Language Processing LK - https://researchspace.csir.co.za PY - 2024 SM - 978-3-031-58494-7 SM - 978-3-031-58495-4 T1 - Text summarisation for low-resourced languages: A review TI - Text summarisation for low-resourced languages: A review UR - http://hdl.handle.net/10204/13690 ER - en_ZA
dc.identifier.worklist 27842 en_US


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