Movie Recommendation System Integrated With YouTube API
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| Natura: | Recurso digital |
| Lingua: | inglese |
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Zenodo
2025
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| _version_ | 1866901287605370880 |
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| author | Rohan, Rajendra Patil Amit Shivaji Powar Mrs. V. S. Mali |
| author_facet | Rohan, Rajendra Patil Amit Shivaji Powar Mrs. V. S. Mali |
| contents | <p>This project focuses on building a movie recommendation system that helps users discover films similar to the ones they already enjoy by using a content-based filtering approach. The system relies on the TMDB dataset, which provides detailed information such as genres, overviews, cast details, and keywords. These features are compared to identify how closely one movie matches another, allowing the system to generate personalized and accurate recommendations. The system is integrated with the YouTube API, enabling users to watch trailers of the recommended movies directly within the platform. This creates a smoother and more interactive movie-exploration experience by combining similarity-based suggestions with instant access to official trailers.</p> <p><strong>Keywords:</strong> Content-Based Filtering, TMDB dataset, Cosine Similarity, Movie Recommendation System, YouTube API, AI</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17714651 |
| institution | Zenodo |
| language | eng |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Movie Recommendation System Integrated With YouTube API Rohan, Rajendra Patil Amit Shivaji Powar Mrs. V. S. Mali Movie Recommendation System Content-Based Filtering TMDB Dataset Cosine Similarity YouTube API Integration Machine Learning Artificial Intelligence <p>This project focuses on building a movie recommendation system that helps users discover films similar to the ones they already enjoy by using a content-based filtering approach. The system relies on the TMDB dataset, which provides detailed information such as genres, overviews, cast details, and keywords. These features are compared to identify how closely one movie matches another, allowing the system to generate personalized and accurate recommendations. The system is integrated with the YouTube API, enabling users to watch trailers of the recommended movies directly within the platform. This creates a smoother and more interactive movie-exploration experience by combining similarity-based suggestions with instant access to official trailers.</p> <p><strong>Keywords:</strong> Content-Based Filtering, TMDB dataset, Cosine Similarity, Movie Recommendation System, YouTube API, AI</p> |
| title | Movie Recommendation System Integrated With YouTube API |
| topic | Movie Recommendation System Content-Based Filtering TMDB Dataset Cosine Similarity YouTube API Integration Machine Learning Artificial Intelligence |
| url | https://doi.org/10.5281/zenodo.17714651 |