AI-Driven Personalization for Content Recommendation in Streaming Platforms

Dr. Kishan Gupta

Abstract


Content recommendation systems are essential for enhancing user engagement in streaming platforms. This paper introduces an AI-driven approach for personalized content recommendation using collaborative filtering and deep learning techniques. The system analyzes user preferences, viewing history, and demographic data to provide tailored recommendations. A hybrid model combining content-based and collaborative filtering methods is developed to overcome challenges such as data sparsity and cold-start problems. Experiments on real-world datasets from streaming services demonstrate improved user satisfaction and engagement. This research highlights the potential of AI in transforming user experiences in digital media platforms.

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