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DOI: 10.14569/IJACSA.2023.0141192
PDF

Quality In-Use of Mobile Geographic Information Systems for Data Collection

Author 1: Badr El Fhel
Author 2: Ali Idri

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 14 Issue 11, 2023.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: Mobile Geographic Information Systems (GIS) plays a vital role in data collection, offering diverse functionalities for spatial data handling. Despite advancements, accurately determining the usage environment during development remains challenging. This study uses machine learning and natural language processing to automatically classify user reviews based on the ISO 25010 quality-in-use model. Motivated by the challenge of gauging user experience during development, stakeholders analyze user reviews for insights. An experimental study compares Support Vector Machine (SVM), Random Forest, Logistic Regression, and Naive Bayes classifiers, revealing superior performance by SVM and Random Forest, particularly in efficiency evaluation. Findings underscore the efficacy of SVM in classifying user reviews, emphasizing its effectiveness in evaluating efficiency within mobile GIS applications. Moreover, it provides valuable insights for stakeholders, contributing to the enhancement of software quality of mobile GIS apps.

Keywords: Mobile GIS for data collection; machine learning; software product quality; ISO/IEC 25010; natural language processing; user experience

Badr El Fhel and Ali Idri, “Quality In-Use of Mobile Geographic Information Systems for Data Collection” International Journal of Advanced Computer Science and Applications(IJACSA), 14(11), 2023. http://dx.doi.org/10.14569/IJACSA.2023.0141192

@article{Fhel2023,
title = {Quality In-Use of Mobile Geographic Information Systems for Data Collection},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0141192},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0141192},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {11},
author = {Badr El Fhel and Ali Idri}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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