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What is Movie Recommendation System Analysis about?

This paper provides a comprehensive analysis of Collaborative Filtering (CF) and its applications in Movie Recommendation Systems (MRS), highlighting its effectiveness in personalizing recommendations based on user preferences. It discusses the two main approaches of CF: memory-based and model-based filtering, and examines the challenges faced by MRS, such as cold start and data sparsity. The study emphasizes the importance of integrating CF with other techniques to enhance recommendation accuracy and user

Author

Abdul Hameed

Language

EN