Feasibility comparison of HAC algorithm on usability performance and self-reported metric features for MAR learning

Kok Cheng Lim, Ali Selamat, Mohd Hazli Mohamed Zabil, Md Hafiz Selamat, Rose Alinda Alias, Fatimah Puteh, Farhan Mohamed, Ondrej Krejcar, Enrique Herrera-Viedma, Hamido Fujita

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper highlights the current literatures in usability studies, performance metrics, self-reported metrics and hierarchical agglomerative clustering algorithms. A literature review is done in these three areas of studies to find a research gap that can be explored further. The paper will then propose a research methodology to study comparatively feature selection based on performance and self-reported usability data. This paper will highlight methods used to compare the feasibility and performance of hierarchical agglomerative clustering algorithms on both performance and self-reported data. The results of the experiment will then be presented and discussed before proceeding to the conclusion and future works of this study.

Original languageEnglish
Title of host publicationNew Trends in Intelligent Software Methodologies, Tools and Techniques - Proceedings of the 17th International Conference, SoMeT 2018
EditorsEnrique Herrera-Viedma, Hamido Fujita
PublisherIOS Press
Pages896-910
Number of pages15
ISBN (Electronic)9781614998990
DOIs
Publication statusPublished - 01 Jan 2018
Event17th International Conference on New Trends in Intelligent Software Methodology Tools and Techniques, SoMeT 2018 - Granada, Spain
Duration: 26 Sep 201828 Sep 2018

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume303
ISSN (Print)0922-6389

Conference

Conference17th International Conference on New Trends in Intelligent Software Methodology Tools and Techniques, SoMeT 2018
CountrySpain
CityGranada
Period26/09/1828/09/18

Fingerprint

Clustering algorithms
Feature extraction
Experiments

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

Cite this

Lim, K. C., Selamat, A., Mohamed Zabil, M. H., Selamat, M. H., Alias, R. A., Puteh, F., ... Fujita, H. (2018). Feasibility comparison of HAC algorithm on usability performance and self-reported metric features for MAR learning. In E. Herrera-Viedma, & H. Fujita (Eds.), New Trends in Intelligent Software Methodologies, Tools and Techniques - Proceedings of the 17th International Conference, SoMeT 2018 (pp. 896-910). (Frontiers in Artificial Intelligence and Applications; Vol. 303). IOS Press. https://doi.org/10.3233/978-1-61499-900-3-896
Lim, Kok Cheng ; Selamat, Ali ; Mohamed Zabil, Mohd Hazli ; Selamat, Md Hafiz ; Alias, Rose Alinda ; Puteh, Fatimah ; Mohamed, Farhan ; Krejcar, Ondrej ; Herrera-Viedma, Enrique ; Fujita, Hamido. / Feasibility comparison of HAC algorithm on usability performance and self-reported metric features for MAR learning. New Trends in Intelligent Software Methodologies, Tools and Techniques - Proceedings of the 17th International Conference, SoMeT 2018. editor / Enrique Herrera-Viedma ; Hamido Fujita. IOS Press, 2018. pp. 896-910 (Frontiers in Artificial Intelligence and Applications).
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Lim, KC, Selamat, A, Mohamed Zabil, MH, Selamat, MH, Alias, RA, Puteh, F, Mohamed, F, Krejcar, O, Herrera-Viedma, E & Fujita, H 2018, Feasibility comparison of HAC algorithm on usability performance and self-reported metric features for MAR learning. in E Herrera-Viedma & H Fujita (eds), New Trends in Intelligent Software Methodologies, Tools and Techniques - Proceedings of the 17th International Conference, SoMeT 2018. Frontiers in Artificial Intelligence and Applications, vol. 303, IOS Press, pp. 896-910, 17th International Conference on New Trends in Intelligent Software Methodology Tools and Techniques, SoMeT 2018, Granada, Spain, 26/09/18. https://doi.org/10.3233/978-1-61499-900-3-896

Feasibility comparison of HAC algorithm on usability performance and self-reported metric features for MAR learning. / Lim, Kok Cheng; Selamat, Ali; Mohamed Zabil, Mohd Hazli; Selamat, Md Hafiz; Alias, Rose Alinda; Puteh, Fatimah; Mohamed, Farhan; Krejcar, Ondrej; Herrera-Viedma, Enrique; Fujita, Hamido.

New Trends in Intelligent Software Methodologies, Tools and Techniques - Proceedings of the 17th International Conference, SoMeT 2018. ed. / Enrique Herrera-Viedma; Hamido Fujita. IOS Press, 2018. p. 896-910 (Frontiers in Artificial Intelligence and Applications; Vol. 303).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - This paper highlights the current literatures in usability studies, performance metrics, self-reported metrics and hierarchical agglomerative clustering algorithms. A literature review is done in these three areas of studies to find a research gap that can be explored further. The paper will then propose a research methodology to study comparatively feature selection based on performance and self-reported usability data. This paper will highlight methods used to compare the feasibility and performance of hierarchical agglomerative clustering algorithms on both performance and self-reported data. The results of the experiment will then be presented and discussed before proceeding to the conclusion and future works of this study.

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Lim KC, Selamat A, Mohamed Zabil MH, Selamat MH, Alias RA, Puteh F et al. Feasibility comparison of HAC algorithm on usability performance and self-reported metric features for MAR learning. In Herrera-Viedma E, Fujita H, editors, New Trends in Intelligent Software Methodologies, Tools and Techniques - Proceedings of the 17th International Conference, SoMeT 2018. IOS Press. 2018. p. 896-910. (Frontiers in Artificial Intelligence and Applications). https://doi.org/10.3233/978-1-61499-900-3-896