Development of a Movie Recommendation System Using Collaborative Filtering
Computer Science — 2025, Undergraduate
recommendation systemmachine learningcollaborative filteringmedia
This study developed a Movie Recommendation System that suggests films to users based on their viewing history and the preferences of similar users. Recommendation Systems reduce the difficulty of discovering relevant content in large catalogues. The system applies collaborative filtering techniques to generate personalised recommendations and lets users rate and provide feedback. Built with Node.js, Express, and MongoDB, the system was evaluated with a sample of users. Findings showed improved discovery of relevant movies and high user satisfaction. The study recommends extension to other content types and refinement of the recommendation algorithm.
For reference and learning only. Do not submit this work as your own.
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