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A Neural Natural Language Processing System for Educational Resource Knowledge Domain Classification

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dc.contributor.authorSchrumpf, Johannes
dc.contributor.authorWeber, Felix
dc.contributor.authorThelen, Tobias
dc.contributor.editorKienle, Andrea
dc.contributor.editorHarrer, Andreas
dc.contributor.editorHaake, Joerg M.
dc.contributor.editorLingnau, Andreas
dc.date.accessioned2021-08-25T08:21:52Z
dc.date.available2021-08-25T08:21:52Z
dc.date.issued2021
dc.description.abstractIn higher education, educational resources are the vessel with which information get transferred to the learner. Information on the content discussed in the scope of the educational resources, however, is implicit and must be inferred by the user by reading the resource title or through contextual information. In this paper we present a state-of-the-art neural natural language processing system, based on Google-BERT, that maps educational resource titles into one of 905 classes from the Dewey Decimal Classification (DDC) system. We present model architecture, training procedure dataset properties and our performance analysis methodology. We show that aside from classification performance, our model implicitly learns the class hierarchy inherent to the DDC.en
dc.identifier.isbn978-3-88579-710-4
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/37023
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofDELFI 2021
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-316
dc.subjectMachine Learning
dc.subjectAI in Higher Education
dc.subjectRecommender Systems
dc.titleA Neural Natural Language Processing System for Educational Resource Knowledge Domain Classificationen
dc.typeText/Conference Paper
gi.citation.endPage288
gi.citation.publisherPlaceBonn
gi.citation.startPage283
gi.conference.date13.-15. September 2021
gi.conference.locationOnline
gi.conference.sessiontitleLernressourcen

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DELFI 2021