The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Digital Archiving Policy
  • Promote your Publication
  • Metadata Harvesting (OAI2)

IJACSA

  • About the Journal
  • Call for Papers
  • Editorial Board
  • Author Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Fees/ APC
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors
  • SUSAI-EE 2025
  • ICONS-BA 2025
  • IoT-BLOCK 2025

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Editorial Board
  • Guidelines
  • Submit
  • Current Issue
  • Archives
  • Indexing
  • Fees
  • Reviewers
  • Subscribe

DOI: 10.14569/IJACSA.2020.0110484
PDF

Machine Learning Model for Personalizing Online Arabic Journalism

Author 1: Nehad Omar
Author 2: Yasser M. K. Omar
Author 3: Fahima A. Maghraby

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 4, 2020.

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

Abstract: The paper discusses a model of generating dynamic profile for Arabic News Users, capturing user preference by analyzing his review of historical news, and recommend him news as soon as he creates account on News Mobile App, Preference is calculated based on article main keywords score, which is extracted from article headline & body as NLP (Natural Language Processing), when user reads an article, its keywords are calculated with rate of interest to his profile. Machine Learning techniques are used in the proposed model to recommend user the relevant news to his preferences and provide him personalization. The model used hybrid filtering techniques to recommend user suitable articles to his preferences, as Content-Based, Collaborative, and Demographic filtering techniques with KNN (K-nearest neighborhood). The model combined between those techniques to enhance the recommendation process, after recommendation happened, that the model tracks User behavior with the recommended articles, whether he reviewed it or not, and the actions he did on the article page to calculate his rate of interest, then dynamically updates his profile in real time with interested keywords score , thus By having User profile and defined preference, the model can help Arabic news publisher to classify users into segments, and track changes in their opinion and inclination, using observation method of read news from different user segments, and which articles attract them, thus it leads publishers to visualize their data and raise their profitability, and to follow the international trend in e-journalism industry to be a data driven organization.

Keywords: Personalization; e-journalism; KNN (K-nearest Neighborhood); dynamic user profile; NLP (Natural Language Processing); data driven organization

Nehad Omar, Yasser M. K. Omar and Fahima A. Maghraby, “Machine Learning Model for Personalizing Online Arabic Journalism” International Journal of Advanced Computer Science and Applications(IJACSA), 11(4), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110484

@article{Omar2020,
title = {Machine Learning Model for Personalizing Online Arabic Journalism},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110484},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110484},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {4},
author = {Nehad Omar and Yasser M. K. Omar and Fahima A. Maghraby}
}



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.

IJACSA

Upcoming Conferences

IntelliSys 2025

28-29 August 2025

  • Amsterdam, The Netherlands

Future Technologies Conference 2025

6-7 November 2025

  • Munich, Germany

Healthcare Conference 2026

21-22 May 2026

  • Amsterdam, The Netherlands

Computing Conference 2026

9-10 July 2026

  • London, United Kingdom

IntelliSys 2026

3-4 September 2026

  • Amsterdam, The Netherlands

Computer Vision Conference 2026

15-16 October 2026

  • Berlin, Germany
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. All rights reserved. Registered in England and Wales. Company Number 8933205. thesai.org