Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/77308
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dc.contributor.authorAtapattu Mudiyanselage, T.-
dc.contributor.authorFalkner, K.-
dc.contributor.authorFalkner, N.-
dc.date.issued2012-
dc.identifier.citationProceedings of the 23rd International Conference on Database and Expert Systems Applications, held in Vienna, 3-6 September, 2012 / S.W. Liddle, K.-D. Schewe, A. Min Tjoa and X. Zhou (eds.): pp.161-175-
dc.identifier.isbn9783642325991-
dc.identifier.issn0302-9743-
dc.identifier.issn1611-3349-
dc.identifier.urihttp://hdl.handle.net/2440/77308-
dc.description.abstractComputer-based educational approaches provide valuable supplementary support to traditional classrooms. Among these approaches, intelligent learning systems provide automated questions, answers, feedback, and the recommendation of further resources. The most difficult task in intelligent system formation is the modelling of domain knowledge, which is traditionally undertaken manually or semi-automatically by knowledge engineers and domain experts. However, this error-prone process is time-consuming and the benefits are confined to an individual discipline. In this paper, we propose an automated solution using lecture notes as our knowledge source to utilise across disciplines. We combine ontology learning and natural language processing techniques to extract concepts and relationships to produce the knowledge representation. We evaluate this approach by comparing the machine-generated vocabularies to terms rated by domain experts, and show a measurable improvement over existing techniques.-
dc.description.statementofresponsibilityThushari Atapattu, Katrina Falkner and Nickolas Falkner-
dc.language.isoen-
dc.publisherSpringer-Verlag-
dc.relation.ispartofseriesLecture Notes in Computer Science; 7446-
dc.rights© Springer, Part of Springer Science+Business Media-
dc.subjectOntology-
dc.subjectPOS tagging-
dc.subjectlecture notes-
dc.subjectconcept extraction-
dc.titleAutomated extraction of semantic concepts from semi-structured data: supporting computer-based education through the analysis of lecture notes-
dc.typeConference paper-
dc.contributor.conferenceInternational Conference on Database and Expert Systems Applications (23rd : 2012 : Vienna)-
dc.identifier.doi10.1007/978-3-642-32600-4_13-
dc.publisher.placeGermany-
pubs.publication-statusPublished-
dc.identifier.orcidAtapattu Mudiyanselage, T. [0000-0002-0632-4482]-
dc.identifier.orcidFalkner, K. [0000-0003-0309-4332]-
dc.identifier.orcidFalkner, N. [0000-0001-7892-6813]-
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Computer Science publications

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