RECSYS 2025, 19th ACM Conference on Recommender Systems, September 22-26, 2025, Prague, Czech Republic
This demo presents an interactive playlist recommendation system that relies exclusively on playlist titles. By fine-tuning a transformerbased language model on clustered playlists, we enable real-time playlist generation for a given title, relying on the semantic meaning
of known playlists’ and tracks’ titles. The playlist title provided in input is freely expressed in natural language in a user-friendly web interface. The system is lightweight, fast, and fully accessible through a simple web page.
Type:
Poster / Demo
City:
Prague
Date:
2025-09-22
Department:
Data Science
Eurecom Ref:
8318
Copyright:
© ACM, 2025. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in RECSYS 2025, 19th ACM Conference on Recommender Systems, September 22-26, 2025, Prague, Czech Republic https://doi.org/10.1145/3705328.3759336
See also:
