Movie and Video Recommendation System using Machine learning

https://doi.org/10.65136/jati.v8i3.92
Machine Learning Recommendation System Item-Based Collaborative Filtering

Authors

  • Shaun Chiang Kum Wah Asia Pacific University of Technology and Innovation (APU) Technology Park Malaysia 57000 Kuala Lumpur, Malaysia
  • Adeline Sneha J
    adeline.john@apu.edu.my
    Asia Pacific University of Technology and Innovation (APU) Technology Park Malaysia 57000 Kuala Lumpur, Malaysia
  • Saif Ahmad Saif Salem Ali Asia Pacific University of Technology and Innovation (APU) Technology Park Malaysia 57000 Kuala Lumpur, Malaysia
  • Leong Jia Jun Asia Pacific University of Technology and Innovation (APU) Technology Park Malaysia 57000 Kuala Lumpur, Malaysia
  • Kamalanathan Shanmugam Asia Pacific University of Technology and Innovation (APU) Technology Park Malaysia 57000 Kuala Lumpur, Malaysia
  • Mohamed Faroug Mohamed Asia Pacific University of Technology and Innovation (APU) Technology Park Malaysia 57000 Kuala Lumpur, Malaysia
Vol. 8 No. 3 (2024)
Original Research
January 13, 2026

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The rise of recommendation systems being implemented in all aspects of our lives requires us to have a basic understanding regarding these algorithms. This study focuses on an item-based collaborative filtering recommendation system used for movies and show recommendations and will provide insight into the parameters used for said recommendation such as genre, rating, and director of the movie/show.