Please use this identifier to cite or link to this item: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/10234
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dc.contributor.authorNadda, Vishal-
dc.contributor.authorkanji, Rakesh [Guided by]-
dc.date.accessioned2023-10-07T10:08:54Z-
dc.date.available2023-10-07T10:08:54Z-
dc.date.issued2023-
dc.identifier.urihttp://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/10234-
dc.descriptionEnrollment No. 191420en_US
dc.description.abstractOver the last couple of years as Natural Language Processing developed immensely, new state of the art language models have pushed the boundaries in all types of benchmark tasks. In this thesis three different extractive summarization models and three different keyword extraction methods were tested and evaluated based on two different quantitative measures and human evaluation to extract information from text. In this paper different techniques for keyword extraction are presented. Keyword extraction is very useful as it helps us to quickly find the relevant text from a large amount of data.en_US
dc.language.isoen_USen_US
dc.publisherJaypee University of Information Technology, Solan, H.P.en_US
dc.subjectVideo verseen_US
dc.subjectNatural language processingen_US
dc.titleVideo verseen_US
dc.typeProject Reporten_US
Appears in Collections:B.Tech. Project Reports

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