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Bereketoglu, Metehan (2023) Movie Recommendation System using Machine Learning. Masters thesis, Dublin, National College of Ireland.
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Abstract
Based on the user’s past actions and preferences, recommendation systems use a variety of algorithms to provide suggestions. They lessen the amount of time users spend searching and provide suggestions for relevant products, which greatly improves their experience and happiness with online interfaces. Likewise, a movie recommendation system may help individuals discover movies they would like quickly—sometimes even without them having to search. Sites like YouTube, Netflix, etc., that have amassed substantial user data often use this approach to play back user-generated content. Using this information, they may train recommendation systems to provide users with movie suggestions based on their interests. Since users can quickly locate the best-rated films in their interest area, this not only enables them to boost viewing length and revenue without advertising, but it also increases user happiness and royalties.
| Item Type: | Thesis (Masters) |
|---|---|
| Supervisors: | Name Email Jilani, Musfira UNSPECIFIED |
| Subjects: | G Geography. Anthropology. Recreation > GV Recreation Leisure Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QA Mathematics > Algebra > Algorithms > Computer algorithms H Social Sciences > HD Industries. Land use. Labor > Specific Industries > Film Industry Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning |
| Divisions: | School of Computing > Master of Science in Data Analytics |
| Depositing User: | Ciara O'Brien |
| Date Deposited: | 07 May 2025 11:22 |
| Last Modified: | 07 May 2025 11:22 |
| URI: | https://norma.ncirl.ie/id/eprint/7499 |
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