• Dr.Bathula Archana
• Dr.S.Shiva Prasad
• M.Deepika
• Mohammed Aftaab Shah Hussain
• Shaik Mazaharun,Sudham Charan Teja

The Personalized Product Recommendation System utilizes collaborative filtering to enhance user engagement by suggesting products based on preferences and behavioral similarities with other users. By analyzing user interactions, the system identifies patterns and recommends items that align with individual interests, ultimately increasing sales. The project focuses on selecting the most effective algorithm for generating tailored recommendations, ensuring a personalized shopping experience. This approach is applicable across various domains, including e-commerce platforms and streaming services, to improve customer satisfaction. Performance metrics are used to evaluate the system’s efficiency and accuracy in delivering relevant suggestions.

Personalized Recommendation System, Collaborative Filtering, Product Recommendation, Behavioral Analysis, Machine Learning.

"Intelligent Personalized Product Recommendation Using Advanced methods", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 3, page no.j450-j455, March-2025, Available :http://www.jetir.org/papers/JETIR2503959.pdf

"Intelligent Personalized Product Recommendation Using Advanced methods", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 3, page no. ppj450-j455, March-2025, Available at : http://www.jetir.org/papers/JETIR2503959.pdf