International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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Movie Recommendation System

Author(s) Md Ayan Ahmad, Sonali Singh
Country India
Abstract In the digital age, movie recommendation systems have become essential for increasing user satisfaction and engagement. In this paper, we present the movie recommendation system based on collaborative filtering, content-based filtering, and a hybrid method to highly customize the suggested movies to the users. Using historical data, analyzing the use’s behaviors of watching preferences, and topics, desired to watch movies, the system recommends movies using advanced machine learning algorithms on what he/she is likely to be interested in.
Keywords Content-based Filtering, Movie Suggestions, Text to vector, vector resemblance, and hybrid methodology
Field Computer
Published In Volume 7, Issue 3, May-June 2025
Published On 2025-05-29
DOI https://doi.org/10.36948/ijfmr.2025.v07i03.43329
Short DOI https://doi.org/g9mnx9
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