Pages and Popcorn: An Adaptive Recommender System for Enhancing Book and Movie Discovery

Author(s)	Mr. Anshul Sahu, Mr. Vikas Garg, Dr. Tapsi Nagpal
Country	India
Abstract	This research presents a comprehensive overview of recommender systems, focusing on their application in book and movie discovery. It explores traditional techniques such as collaborative and content-based filtering, as well as advanced approaches involving hybrid models, deep learning, reinforcement learning, and knowledge graphs. The study discusses key challenges including data sparsity, cold-start problems, bias, scalability, and privacy concerns. By analyzing current methodologies and implementation strategies, the paper aims to highlight how intelligent recommendation engines can enhance user experience and personalization in digital platforms.
Keywords	Recommender system, Machine learning, Content-based filtering, Collaborative filtering, hybrid recommenders
Field	Engineering
Published In	Volume 16, Issue 3, July-September 2025
Published On	2025-07-05

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