Tune based music playlist continuationKosi, Miha (Avtor) Sadikov, Aleksander (Mentor) Felfernig, Alexander (Komentor) playlist continuationmusic information retrievalrecommendation systemMusic streaming services have become a key part of the music industry in recent years. Among other things, they allow users to create their own playlists and continue them with similar tracks after the last track ends, but these are not always relevant. We aimed to improve the relevance of recommended tracks in playlist continuation using tune-based recommendation. Our solution is based on the similarity of note sequences of different tracks. We present the entire workflow of our solution, from candidate selection and music transcription to the measurement of the similarity between the tracks. Unfortunately, our solution did not achieve satisfactory results and also has a high time complexity, therefore we do not consider it suitable for playlist continuation in a real-world scenario. However, we believe that our method has potential in other areas of use, such as detecting plagiarism in music.20232023-09-29 14:05:00Magistrsko delo/naloga151109sl