Publication: Comparing the Accuracy of Hierarchical Agglomerative and K-means Clustering on Mobile Augmented Reality Usability Metrics
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Date
2019
Authors
Cheng L.K.
Selamat A.
Zabil M.H.M.
Selamat M.H.
Alias R.A.
Puteh F.
Mohamed F.
Krejcar O.
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers Inc.
Abstract
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.
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