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dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorJansen, Slinger
dc.contributor.authorConstantinou, Alexandros
dc.date.accessioned2024-12-27T00:00:55Z
dc.date.available2024-12-27T00:00:55Z
dc.date.issued2024
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/48264
dc.description.abstractThis project focuses on the automatic software features extraction from vendors' webpages and the consequent creation of a knowledge graph to accommodate these features. The use of LLMs for the classification of features is explored, through prompt engineering and few-shot learning, which is compared to traditional supervised learning techniques.
dc.description.sponsorshipUtrecht University
dc.language.isoEN
dc.subjectAutomatic software product features extraction from software vendor documents
dc.titleAutomatic software product features extraction from software vendor documents
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.keywordsknowledge graphs; software features; information retrieval; knowledge retrieval
dc.subject.courseuuArtificial Intelligence
dc.thesis.id41741


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