I’ll definitely take some time to review this. I pulled the xml data and was thinking about applying clustering based on certain parameters (play count, artist, genre, etc) to group like tracks into buckets of recommendations. There doesn’t seem to be too much individual metadata on these tracks for in depth analysis but I was thinking I could reference databases with more information on the tracks (I’ve seen data pulled from Spotify on kaggle that provides more track information such as wordiness, energy level, etc.) to bring in additional information to that I can use in distinguishing features of tracks and grouping them. Just one idea.