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@article{171780,
        author = {Pooja Naganath Lamkane},
        title = {MOVIE RECOMMENDATION SYSTEM},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {8},
        pages = {3496-3499},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=171780},
        abstract = {The Movie Recommendation System is a machine learning-based application that provides personalized movie recommendations to users. It utilizes collaborative filtering techniques to analyze user preferences and similarities among movies generate accurate and relevant recommendation. A movie recommendation system’s main objective is to improve user’s movie watching experiences by assisting them in finding movies they are likely to like. Users can rely on the system to get specialized recommendation that match their tastes and preferences rather than manually looking vast library of films. This project aims to improve user or viewer satisfaction by simplifying access to service while reducing administrative complexity for business. As well as, MOVIE RECOMMENDATION SYSTEM, is a type of machine learning application designed to suggest movies to user or viewer based on their preferences and their behaviour. These system helps to enhance user experience by personalizing suggestions, often using large data sets of users’ interaction and movie metadata. A well-designed system can enhance user engagement, retention, and satisfaction, making it a critical tool in the entertainment industry.},
        keywords = {movie Recognition, Machine Learning, Real-Time Processing.},
        month = {February},
        }