Transforming Movie Recommendations with Advanced Machine Learning: A Study of NMF, SVD,and K-Means Clustering

• URL: http://arxiv.org/abs/2407.08916v1
• Date: Fri, 12 Jul 2024 01:26:33 GMT
• Title: Transforming Movie Recommendations with Advanced Machine Learning: A Study of NMF, SVD,and K-Means Clustering
• Authors: Yubing Yan, Camille Moreau, Zhuoyue Wang, Wenhan Fan, Chengqian Fu,
• Abstract summary: This study develops a robust movie recommendation system using various machine learning techniques. The primary objective is to enhance user experience by providing personalized movie recommendations.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This study develops a robust movie recommendation system using various machine learning techniques, including Non- Negative Matrix Factorization (NMF), Truncated Singular Value Decomposition (SVD), and K-Means clustering. The primary objective is to enhance user experience by providing personalized movie recommendations. The research encompasses data preprocessing, model training, and evaluation, highlighting the efficacy of the employed methods. Results indicate that the proposed system achieves high accuracy and relevance in recommendations, making significant contributions to the field of recommendations systems.

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