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@article{200903,
        author = {Malhar Kulkarni and Ayush Patil and Khsitij raj and Mayuresh Gulame and Aarti Pimpalkar},
        title = {MovieMate: An AI-Based Cross-Platform Personalized Movie Recommender},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {2677-2681},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=200903},
        abstract = {The exponential growth of Over-The-Top (OTT) streaming platforms has resulted in an overwhelming abundance of digital content, significantly complicating the process of efficient movie discovery. Users are frequently confronted with large volumes of choices, yet existing recommendation systems remain largely constrained to individual platforms and rely on limited user interaction signals. These systems often fail to incorporate essential contextual parameters such as emotional state, temporal availability, and social engagement patterns.
To overcome these limitations, this paper presents MovieMate, an advanced artificial intelligence-based cross-platform movie recommendation framework designed to deliver highly adaptive and context-aware suggestions. The system integrates multiple recommendation paradigms, including collaborative filtering, content-based filtering, and mood-driven intelligence, to construct a comprehensive understanding of user behavior.
Additionally, MovieMate leverages external movie metadata through the TMDb API and incorporates user interaction signals such as watch history, preferences, and social connections. Experimental analysis demonstrates a significant improvement in system performance, including a 37% reduction in content discovery time, an increase in recommendation accuracy up to 89%, and a 2.3× enhancement in user engagement. These findings highlight the effectiveness of the proposed system in addressing the challenges of modern content discovery across multiple streaming platforms.},
        keywords = {AI Recommender, MovieMate, Cross-Platform, Personalization, Streaming, Collaborative Filtering, Mood-Based Suggestions, TMDb, React, Tailwind},
        month = {May},
        }