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Mobile Devices Interface Adaptivity Using Ontologies

Muhammad Waseem Iqbal1, Muhammad Raza Naqvi2, Muhammad Adnan Khan3,4, Faheem Khan5, T. Whangbo5,*

1 Department of Software Engineering, The Superior University, Lahore, 53700, Pakistan
2 INP-ENIT, University of Toulouse, Tarbes, 65000, France
3 Riphah School of Computing & Innovation, Faculty of Computing, Riphah International University Lahore Campus, Lahore, 54000, Pakistan
4 Pattern Recognition and Machine Learning Lab, Department of Software, Gachon University, Seongnam, 13557, Korea
5 Department of Computer Engineering, Gachon University, Seongnam, 13557, Korea

* Corresponding Author: T. Whangbo. Email: email

Computers, Materials & Continua 2022, 71(3), 4767-4784. https://doi.org/10.32604/cmc.2022.023239

Abstract

Currently, many mobile devices provide various interaction styles and modes which create complexity in the usage of interfaces. The context offers the information base for the development of Adaptive user interface (AUI) frameworks to overcome the heterogeneity. For this purpose, the ontological modeling has been made for specific context and environment. This type of philosophy states to the relationship among elements (e.g., classes, relations, or capacities etc.) with understandable satisfied representation. The context mechanisms can be examined and understood by any machine or computational framework with these formal definitions expressed in Web ontology language (WOL)/Resource description frame work (RDF). The Protégé is used to create taxonomy in which system is framed based on four contexts such as user, device, task and environment. Some competency questions and use-cases are utilized for knowledge obtaining while the information is refined through the instances of concerned parts of context tree. The consistency of the model has been verified through the reasoning software while SPARQL querying ensured the data availability in the models for defined use-cases. The semantic context model is focused to bring in the usage of adaptive environment. This exploration has finished up with a versatile, scalable and semantically verified context learning system. This model can be mapped to individual User interface (UI) display through smart calculations for versatile UIs.

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Cite This Article

APA Style
Iqbal, M.W., Naqvi, M.R., Khan, M.A., Khan, F., Whangbo, T. (2022). Mobile devices interface adaptivity using ontologies. Computers, Materials & Continua, 71(3), 4767-4784. https://doi.org/10.32604/cmc.2022.023239
Vancouver Style
Iqbal MW, Naqvi MR, Khan MA, Khan F, Whangbo T. Mobile devices interface adaptivity using ontologies. Comput Mater Contin. 2022;71(3):4767-4784 https://doi.org/10.32604/cmc.2022.023239
IEEE Style
M.W. Iqbal, M.R. Naqvi, M.A. Khan, F. Khan, and T. Whangbo, “Mobile Devices Interface Adaptivity Using Ontologies,” Comput. Mater. Contin., vol. 71, no. 3, pp. 4767-4784, 2022. https://doi.org/10.32604/cmc.2022.023239



cc Copyright © 2022 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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