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Term Extraction for Domain Modeling

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dc.contributor.authorKruse, Theresa
dc.contributor.authorLohr, Dominic
dc.contributor.authorBerges, Marc
dc.contributor.authorKohlhase, Michael
dc.contributor.authorMoghbeli, Halimeh
dc.contributor.authorSchütz, Marcel
dc.contributor.editorSchulz, Sandra
dc.contributor.editorKiesler, Natalie
dc.date.accessioned2024-09-03T16:26:19Z
dc.date.available2024-09-03T16:26:19Z
dc.date.issued2024
dc.description.abstractAdaptive learning systems need to use domain and learner models to provide meaningful support for learners. Building fine-grained domain models by hand is very time-consuming, so the demand for partial automation is high. This paper investigates how term extraction tools can support constructing a domain model. Therefore, we study if different automatic term extraction tools give comparable results to a human annotator. Our results show that the current extraction tools support the process, but their results are not directly usable and still need human adjustments.en
dc.identifier.doi10.18420/delfi2024_33
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/44516
dc.language.isoen
dc.pubPlaceBonn
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofProceedings of DELFI 2024
dc.relation.ispartofseriesDELFI
dc.subjectdomain modeling
dc.subjectterm extraction
dc.subjectadaptive learning system
dc.subjectprogramming
dc.titleTerm Extraction for Domain Modelingen
dc.typeText/Conference paper
mci.conference.date09.-11. September 2024
mci.conference.locationFulda
mci.conference.sessiontitleKI Einsatz in der Hochschule II
mci.document.qualitydigidoc
mci.reference.pages369-377

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