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IJARSAI Int. J. Adv. Res. Sci. Anal. Infer.
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Article Dates: Received: 05 Aug 2024| Revised Submission: 10 Sep 2024 | Accepted: 05 Dec 2024| Available Online: 15 Mar 2025
Abstract
Keywords: Machine Learning, Recommendation Systems, Natural Language Processing, Cosine Similarity, TF-IDF, Support Vector Machines, Comparative Study, Netflix Data
How to Cite:M. S., Praseetha, & Shine, T. (2025). Enhancing personalization in recommendation systems: A comparative study of machine learning models on Netflix data. IJARSAI International Journal of Advanced Research Scientific Analysis & Inferences, 1(1), 22–40. https://doi.org/10.5281/zenodo.16197720
Praseetha M.S.
Assistant Professor
Department of Computer Applications
SCMS School of Technology and Management
Kochi, Kerala
Email:praseetha@scmsgroup.org
Tania Shine
Scholar, SCMS School of Technology and Management
Kochi, Kerala
Email: taniashine06@gmail.com
Article Dates: Received: 05 Aug 2024| Revised Submission: 10 Sep 2024 | Accepted: 05 Dec 2024| Available Online: 15 Mar 2025
Abstract
In this research paper the authors try to present a comprehensive study on the development and evaluation of a personalized content recommendation system for the Netflix platform. Various machine learning models were implemented and compared using metrics such as accuracy, recall, F1-score, and precision, to enhance the accuracy and effectiveness of content recommendations. The study encompasses various machine learning techniques, including TF-IDF, Cosine Similarity, Support Vector Machines (SVM), K Nearest Neighbors (KNN), and Nearest Neighbors, to build a hybrid model. The study provides valuable insights into the strengths and limitations of different models applied to the recommendation systems and also enhances personalization by the utilization of hybrid models.
Keywords: Machine Learning, Recommendation Systems, Natural Language Processing, Cosine Similarity, TF-IDF, Support Vector Machines, Comparative Study, Netflix Data
How to Cite:M. S., Praseetha, & Shine, T. (2025). Enhancing personalization in recommendation systems: A comparative study of machine learning models on Netflix data. IJARSAI International Journal of Advanced Research Scientific Analysis & Inferences, 1(1), 22–40. https://doi.org/10.5281/zenodo.16197720
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