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DOI: 10.14569/IJACSA.2020.0110906
PDF

A Recommender System for Mobile Applications of Google Play Store

Author 1: Ahlam Fuad
Author 2: Sahar Bayoumi
Author 3: Hessah Al-Yahya

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 9, 2020.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: With the growth in the smartphone market, many applications can be downloaded by users. Users struggle with the availability of a massive number of mobile applications in the market while finding a suitable application to meet their needs. Indeed, there is a critical demand for personalized application recommendations. To address this problem, we propose a model that seamlessly combines content-based filtering with application profiles. We analyzed the applications available on the Google Play app store to extract the essential features for choosing an app and then used these features to build app profiles. Based on the number of installations, the number of reviews, app size, and category, we developed a content-based recommender system that can suggest some apps for users based on what they have searched for in the application’s profile. We tested our model using a k-nearest neighbor algorithm and demonstrated that our system achieved good and reasonable results.

Keywords: Application profile; content-based filtering; Google play; mobile applications; recommender systems

Ahlam Fuad, Sahar Bayoumi and Hessah Al-Yahya, “A Recommender System for Mobile Applications of Google Play Store” International Journal of Advanced Computer Science and Applications(IJACSA), 11(9), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110906

@article{Fuad2020,
title = {A Recommender System for Mobile Applications of Google Play Store},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110906},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110906},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {9},
author = {Ahlam Fuad and Sahar Bayoumi and Hessah Al-Yahya}
}



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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