In the Music Recommendation System, there are two main actors: User and Recommendation Engine. The User can register, log in, browse the music catalog, listen to songs, like songs, save songs to playlists, view personalized recommendations, search for music, rate songs, and manage their profile. These interactions provide the system with valuable data about the user’s preferences. The Recommendation Engine uses this data to generate tailored music recommendations. Actions like liking, rating, and saving songs to playlists directly influence the recommendation generation, helping users discover new music that matches their tastes.
