• Mr. Shravan
• Dr. Shashidhar Kini K

In the digital era, music consumption has evolved from physical formats to on-demand digital streaming platforms. Personalization has become a central component in enhancing user engagement and satisfaction. This paper presents a Phase 1 report on the development of a scalable, full-stack Music Recommendation System using the MERN stack (MongoDB, Express.js, React.js, Node.js). The platform aims to recommend personalized music to users based on listening behavior, mood, and preferences. Key features include user registration, playlist management, genre filtering, mood-based discovery, and basic collaborative filtering. The paper discusses the architecture, design methodology, backend logic, and testing outcomes of this intelligent music recommendation platform.

Music recommendation, MERN stack, collaborative filtering, web application, user experience, personalization.

"MUSIC RECOMMENDATION SYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 7, page no.1020-1024, July-2025, Available :http://www.jetir.org/papers/JETIRGX06191.pdf

"MUSIC RECOMMENDATION SYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 7, page no. pp1020-1024, July-2025, Available at : http://www.jetir.org/papers/JETIRGX06191.pdf