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A comparative usability study using Hierarchical Agglomerative and K-means clustering on Mobile Augmented reality interaction data

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dc.citedby1
dc.contributor.authorLim K.C.en_US
dc.contributor.authorSelamat A.en_US
dc.contributor.authorMohamed Zabil M.H.en_US
dc.contributor.authorYusoff Y.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.authorid57188850203en_US
dc.contributor.authorid24468984100en_US
dc.contributor.authorid35185866500en_US
dc.contributor.authorid56921898900en_US
dc.contributor.authorid57215520379en_US
dc.contributor.authorid25928253600en_US
dc.contributor.authorid57202529348en_US
dc.contributor.authorid55416008900en_US
dc.contributor.authorid14719632500en_US
dc.date.accessioned2023-05-29T07:23:57Z
dc.date.available2023-05-29T07:23:57Z
dc.date.issued2019
dc.descriptionAugmented reality; Hierarchical clustering; Learning systems; Machine learning; Usability engineering; Hierarchical agglomerative clustering; K-means; Performance metrics; Self-reported metrics; Usability; K-means clusteringen_US
dc.description.abstractThis article presents the experimental work of comparing the performances of two machine learning approaches, namely Hierarchical Agglomerative clustering and K-means clustering on Mobile Augmented Reality Usability datasets. The datasets comprises of 2 separate categories of data, namely performance and self-reported, which are completely different in nature, techniques and affiliated biases. This research will first present the background and related literature before presenting initial findings of identified problems and objectives. This paper will the present in detail the proposed methodology before presenting the evidences and discussion of comparing this two widely used machine learning approach on usability data. This paper contributes in presenting evidences showing K-means as the better performing clustering algorithm when compared to Hierarchical Agglomerative when implemented on the usability datasets. The results shown has contradicted with some recent studies claiming otherwise, and the findings have created more research gaps pertaining the combined utilization of machine learning and usability analysis. � 2019 The authors and IOS Press. All rights reserved.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.3233/FAIA190054
dc.identifier.epage271
dc.identifier.scopus2-s2.0-85082049921
dc.identifier.spage258
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85082049921&doi=10.3233%2fFAIA190054&partnerID=40&md5=3ccabc6cdc5a7f22661a740a94b4bc7c
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/24490
dc.identifier.volume318
dc.publisherIOS Pressen_US
dc.sourceScopus
dc.sourcetitleFrontiers in Artificial Intelligence and Applications
dc.titleA comparative usability study using Hierarchical Agglomerative and K-means clustering on Mobile Augmented reality interaction dataen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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