An Algorithm for Generating Gap-Fill Multiple Choice Questions of an Expert System

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dc.contributor.authorSirithumgul, Pornpat
dc.contributor.authorPrasertsilp, Pimpaka
dc.contributor.authorOlfman, Lorne
dc.date.accessioned2021-12-24T18:28:34Z
dc.date.available2021-12-24T18:28:34Z
dc.date.issued2022-01-04
dc.description.abstractThis research is aimed to propose an artificial intelligence algorithm comprising an ontology-based design, text mining, and natural language processing for automatically generating gap-fill multiple choice questions (MCQs). The simulation of this research demonstrated an application of the algorithm in generating gap-fill MCQs about software testing. The simulation results revealed that by using 103 online documents as inputs, the algorithm could automatically produce more than 16 thousand valid gap-fill MCQs covering a variety of topics in the software testing domain. Finally, in the discussion section of this paper we suggest how the proposed algorithm should be applied to produce gap-fill MCQs being collected in a question pool used by a knowledge expert system.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2022.901
dc.identifier.isbn978-0-9981331-5-7
dc.identifier.urihttp://hdl.handle.net/10125/80243
dc.language.isoeng
dc.relation.ispartofProceedings of the 55th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectComputational Intelligence and State-of-the-Art Data Analytics
dc.subjectartificial intelligence (ai) for knowledge processing
dc.subjectexpert system
dc.subjectnatural language processing (nlp)
dc.subjectontology-based design
dc.subjecttext mining
dc.titleAn Algorithm for Generating Gap-Fill Multiple Choice Questions of an Expert System
dc.type.dcmitext

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