

Genre-Based Movie Recommendation using Python Flask and JSON Dataset
Abstract
With the vast growth of digital content, especially in the entertainment industry, users often struggle to find relevant movies tailored to their tastes. A lightweight Movie Recommendation System is designed to address this by offering genre-based filtering, rating-based sorting, and keyword search in real time. Built using Python Flask, HTML/CSS, and JavaScript, the system uses a JSON dataset and delivers movie suggestions in a responsive and user-friendly format. This approach draws on recent advances in personalized filtering and recommendation system design [1,2].
References
Pappala, S. (2024). Sentiment-driven movie recommendation system. International Journal of Future Research, 11(4), 45–52.
Xia, L., Chen, W., Li, Y., & Zhang, X. (2024). Movie recommendation with poster attention via multi-modal transformer feature fusion. arXiv preprint arXiv:2402.03219.
Yan, Y., Wang, J., & Zhao, K. (2024). Transforming movie recommendations with advanced machine learning. arXiv preprint arXiv:2401.07856.
Nesmaoui, R., Zineddine, A., & Boubekeur, M. (2023). Collaborative filtering using graph neural network. arXiv preprint arXiv:2310.05823.
Tavakol, M., & Sadeghi, A. (2023). Graph neural network for movie recommendation. IEEE Transactions on Neural Networks and Learning Systems. Advance online publication. https://doi.org/10.1109/TNNLS.2023.XXXXX (replace with actual DOI if available)
Sanke, M., Thakkar, K., & Desai, V. (2023). Movie recommendation using deep learning. International Journal of Computer Applications, 176(20), 1–6.
Zhang, H., & Liu, Y. (2022). Deep learning-based hybrid recommender system for video streaming platforms. IEEE Access, 10, 5589–5602.
Abolghasemi, R., Fazlollahtabar, H., & Zarandi, M. H. (2022). Personality-aware group recommendation system using type theory and fuzzy logic. Information Sciences, 586, 516–535.
Zhang, K., Lin, J., & Xu, W. (2022). Collaborative filtering with neural attention networks for recommendation. Expert Systems with Applications, 196, 116620.
Mehta, I., & Kamdar, A. (2022). Composite ranking-based movie recommendation. International Journal of Innovative Science and Research Technology, 7(4), 1146–1150.
Refbacks
- There are currently no refbacks.