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Term Extraction for Domain Modeling

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2024

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Gesellschaft für Informatik e.V.

Abstract

Adaptive 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.

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Kruse, Theresa; Lohr, Dominic; Berges, Marc; Kohlhase, Michael; Moghbeli, Halimeh; Schütz, Marcel (2024): Term Extraction for Domain Modeling. Proceedings of DELFI 2024. DOI: 10.18420/delfi2024_33. Gesellschaft für Informatik e.V.

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domain modeling, term extraction, adaptive learning system, programming

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