Many businesses enhance on-line user experience using various recommender systems which have a growing innovation and research interest. Recommender systems in music streaming applications proactively suggest new selections to users by attempting to predict user preferences. While current music recommendation systems help users to efficiently discover fascinating music, challenges remain in this research area. This paper presents a critical analysis of current music recommender systems and proposes a new hybrid recommender system with efficient and enhanced prediction capabilities.

With the increasing demand for applications supporting mobility, well-structured and competent mobile applications are a growing need. The music industry is one of the prominent sectors which is expanding its services to mobile platforms. This paper presents a novel design of a Mobile Music Streaming Application which provides music streaming services to users efficiently and effectively.