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Feasibility comparison of HAC algorithm on usability performance and self-reported metric features for MAR learning

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dc.citedby2
dc.contributor.authorCheng L.K.en_US
dc.contributor.authorSelamat A.en_US
dc.contributor.authorZabil M.H.M.en_US
dc.contributor.authorSelamat M.H.en_US
dc.contributor.authorAlias R.A.en_US
dc.contributor.authorPuteh F.en_US
dc.contributor.authorMohamed F.en_US
dc.contributor.authorKrejcar O.en_US
dc.contributor.authorHerrera-Viedma E.en_US
dc.contributor.authorFujita H.en_US
dc.contributor.authorid57188850203en_US
dc.contributor.authorid24468984100en_US
dc.contributor.authorid35185866500en_US
dc.contributor.authorid57215520379en_US
dc.contributor.authorid25928253600en_US
dc.contributor.authorid57202529348en_US
dc.contributor.authorid55416008900en_US
dc.contributor.authorid14719632500en_US
dc.contributor.authorid7004240703en_US
dc.contributor.authorid35611951900en_US
dc.date.accessioned2023-05-29T06:53:49Z
dc.date.available2023-05-29T06:53:49Z
dc.date.issued2018
dc.descriptionAugmented reality; Cluster analysis; Learning systems; Usability engineering; Agglomerative clustering; English language teaching; Mobile augmented reality; Unsupervised machine learning; Usability; Clustering algorithmsen_US
dc.description.abstractThis paper highlights the current literatures in usability studies, performance metrics, self-reported metrics and hierarchical agglomerative clustering algorithms. A literature review is done in these three areas of studies to find a research gap that can be explored further. The paper will then propose a research methodology to study comparatively feature selection based on performance and self-reported usability data. This paper will highlight methods used to compare the feasibility and performance of hierarchical agglomerative clustering algorithms on both performance and self-reported data. The results of the experiment will then be presented and discussed before proceeding to the conclusion and future works of this study. � 2018 The authors and IOS Press. All rights reserved.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.3233/978-1-61499-900-3-896
dc.identifier.epage910
dc.identifier.scopus2-s2.0-85063371964
dc.identifier.spage896
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85063371964&doi=10.3233%2f978-1-61499-900-3-896&partnerID=40&md5=9c72d727ad676ea7143553e5d7e09813
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/23979
dc.identifier.volume303
dc.publisherIOS Pressen_US
dc.sourceScopus
dc.sourcetitleFrontiers in Artificial Intelligence and Applications
dc.titleFeasibility comparison of HAC algorithm on usability performance and self-reported metric features for MAR learningen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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