Publication: Quantifying usability prioritization using K-means clustering algorithm on hybrid metric features for MAR learning
Date
2019
Authors
Lim K.C.
Selamat A.
Mohamed Zabil M.H.
Selamat M.H.
Alias R.A.
Puteh F.
Mohamed F.
Krejcar O.
Journal Title
Journal ISSN
Volume Title
Publisher
IOS Press
Abstract
This paper presents and discusses an empirical work of using machine learning K-means clustering algorithm in analyzing and processing Mobile Augmented Reality (MAR) learning usability data. This paper first discusses the issues within usability and machine learning spectrum, then explain in detail a proposed methodology approaching the experiments conducted in this research. This contributes in providing empirical evidence on the feasibility of K-means algorithm through the discreet display of preliminary outcomes and performance results. This paper also proposes a new usability prioritization technique that can be quantified objectively through the calculation of negative differences between cluster centroids. Towards the end, this paper will discourse important research insights, impartial discussions and future works. � 2019 The authors and IOS Press. All rights reserved.
Description
Augmented reality; Learning algorithms; Machine learning; Usability engineering; Between clusters; Mobile augmented reality; Prioritization; Prioritization techniques; Unsupervised machine learning; Usability; K-means clustering