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Comparing the Accuracy of Hierarchical Agglomerative and K-means Clustering on Mobile Augmented Reality Usability Metrics

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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.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.date.accessioned2023-05-29T07:22:46Z
dc.date.available2023-05-29T07:22:46Z
dc.date.issued2019
dc.descriptionAugmented reality; Big data; 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. � 2019 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo8987044
dc.identifier.doi10.1109/ICBDA47563.2019.8987044
dc.identifier.epage40
dc.identifier.scopus2-s2.0-85080864631
dc.identifier.spage34
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85080864631&doi=10.1109%2fICBDA47563.2019.8987044&partnerID=40&md5=3ea65dcd46a236b4964575ffb20a9679
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/24322
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitle2019 IEEE Conference on Big Data and Analytics, ICBDA 2019
dc.titleComparing the Accuracy of Hierarchical Agglomerative and K-means Clustering on Mobile Augmented Reality Usability Metricsen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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