Publication: A comparative study of major clustering techniques for MAR learning usability prioritization processes
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Date
2020
Authors
Lim K.C.
Selamat A.
Mohamed Zabil M.H.
Selamat M.H.
Alias R.A.
Mohamed F.
Krejcar O.
Journal Title
Journal ISSN
Volume Title
Publisher
IOS Press BV
Abstract
This paper presents and discusses a comparative study of three major clustering categories namely Hierarchical-based, Iterative mode-based and Partition-based in analyzing and prioritizing Mobile Augmented reality (MAR) Learning (MAR-learning) usability data. This paper first discusses the related works in usability and clustering before moving on to the identification of gaps that can be addressed through experimentation. This paper will then propose a research methodology to measure four common clustering techniques on MAR-learning usability data. The paper will then discourse comparative results showing how Mini-batch K-means to be an ideal technique within the experimental setup. The paper will then present important research highlights, discussion, conclusion and future works. � 2020 The authors and IOS Press. All rights reserved.
Description
Augmented reality; Hierarchical clustering; Usability engineering; Clustering techniques; Comparative studies; K-means; Mobile augmented reality; Mode-based; Prioritization process; Related works; Research methodologies; Iterative methods