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

Augmented reality; Big data; Hierarchical clustering; Learning systems; Machine learning; Usability engineering; Hierarchical agglomerative clustering; K-means; Performance metrics; Self-reported Metrics; Usability; K-means clustering

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Bibliographic Details
Main Authors: Cheng L.K., Selamat A., Zabil M.H.M., Selamat M.H., Alias R.A., Puteh F., Mohamed F., Krejcar O.
Other Authors: 57188850203
Format: Conference Paper
Published: Institute of Electrical and Electronics Engineers Inc. 2023
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spelling my.uniten.dspace-243222023-05-29T15:22:46Z Comparing the Accuracy of Hierarchical Agglomerative and K-means Clustering on Mobile Augmented Reality Usability Metrics Cheng L.K. Selamat A. Zabil M.H.M. Selamat M.H. Alias R.A. Puteh F. Mohamed F. Krejcar O. 57188850203 24468984100 35185866500 57215520379 25928253600 57202529348 55416008900 14719632500 Augmented reality; Big data; Hierarchical clustering; Learning systems; Machine learning; Usability engineering; Hierarchical agglomerative clustering; K-means; Performance metrics; Self-reported Metrics; Usability; K-means clustering This 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. Final 2023-05-29T07:22:46Z 2023-05-29T07:22:46Z 2019 Conference Paper 10.1109/ICBDA47563.2019.8987044 2-s2.0-85080864631 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85080864631&doi=10.1109%2fICBDA47563.2019.8987044&partnerID=40&md5=3ea65dcd46a236b4964575ffb20a9679 https://irepository.uniten.edu.my/handle/123456789/24322 8987044 34 40 Institute of Electrical and Electronics Engineers Inc. Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Augmented reality; Big data; Hierarchical clustering; Learning systems; Machine learning; Usability engineering; Hierarchical agglomerative clustering; K-means; Performance metrics; Self-reported Metrics; Usability; K-means clustering
author2 57188850203
author_facet 57188850203
Cheng L.K.
Selamat A.
Zabil M.H.M.
Selamat M.H.
Alias R.A.
Puteh F.
Mohamed F.
Krejcar O.
format Conference Paper
author Cheng L.K.
Selamat A.
Zabil M.H.M.
Selamat M.H.
Alias R.A.
Puteh F.
Mohamed F.
Krejcar O.
spellingShingle Cheng L.K.
Selamat A.
Zabil M.H.M.
Selamat M.H.
Alias R.A.
Puteh F.
Mohamed F.
Krejcar O.
Comparing the Accuracy of Hierarchical Agglomerative and K-means Clustering on Mobile Augmented Reality Usability Metrics
author_sort Cheng L.K.
title Comparing the Accuracy of Hierarchical Agglomerative and K-means Clustering on Mobile Augmented Reality Usability Metrics
title_short Comparing the Accuracy of Hierarchical Agglomerative and K-means Clustering on Mobile Augmented Reality Usability Metrics
title_full Comparing the Accuracy of Hierarchical Agglomerative and K-means Clustering on Mobile Augmented Reality Usability Metrics
title_fullStr Comparing the Accuracy of Hierarchical Agglomerative and K-means Clustering on Mobile Augmented Reality Usability Metrics
title_full_unstemmed Comparing the Accuracy of Hierarchical Agglomerative and K-means Clustering on Mobile Augmented Reality Usability Metrics
title_sort comparing the accuracy of hierarchical agglomerative and k-means clustering on mobile augmented reality usability metrics
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2023
_version_ 1806426412784025600
score 13.18916

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