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Term Extraction for Domain Modeling

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.
Publication Type
ConferencePaper
Author
Kruse-Kurbach, Theresa 
•
Lohr, Dominic 
•
Berges, Marc 
•
Kohlhase, Michael 
•
Moghbeli, Halimeh 
•
Schütz, Marcel 
Date Issued
2024
DOI
10.18420/DELFI2024_33
Faculty
Externe Einrichtung
Institute / Institution
Externe Einrichtung
Published in
DELFI 2024: Die 22. Fachtagung Bildungstechnologien der Gesellschaft für Informatik e.V.
Conference
22. Fachtagung Bildungstechnologien, Fulda, 09.09.-11.09.2024
Publisher
Gesellschaft für Informatik e.V.
Publisher Place
Bonn
Page Start
369
Page End
377
Series Name
GI-Edition - Lecture Notes in Informatics (LNI). Proceedings
Issue Number
P-356
ISBN
978-3-88579-255-0
HilPub short link
https://hilpub.uni-hildesheim.de/handle/ubhi/17855
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