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@article{175447,
        author = {Benu Gopal Panday and Vipul Kunwar and Rohit Kumar Prince and Mr. Alok Kumar},
        title = {Movie Recommendation System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {8096-8101},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=175447},
        abstract = {In this project, a movie recommendation system is built based on the TMDB datasets. We used a content-based filtering method to recommend other movies that are similar to the selected movies. The movie recommendation algorithm already has enough stuff available. Presenting the suggested films is crucial.  in order to save the user time when looking for the stuff that he or she might find appealing. As a result, the movie recommendation system is essential for providing users with tailored movie recommendations. Following extensive web research and consulting numerous research papers, we discovered that the suggestions provided by content-based filtering employ a single text-to-vector conversion method and a single method to identify the correspondence between the vectors. Several texts were converted using vector conversion techniques in this study, and the final suggestion list was obtained by manipulating the output of several algorithms. It can be viewed as a hybrid strategy that solely uses the content-based filtering technique.},
        keywords = {},
        month = {May},
        }