What is it about?
This work presents a playlist generation system that relies solely on the playlist title. By fine-tuning a sentence transformer on clustered playlists, it captures the semantic meaning of titles to recommend tracks that match their theme, mood, or context.
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Why is it important?
Playlist titles contain rich semantic cues often ignored by traditional recommenders. Leveraging them enables effective cold-start recommendations and more personalized, context-aware music discovery—bridging the gap between language understanding through AI and recommendation systems.
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This page is a summary of: A Language Model-Based Playlist Generation Recommender System, September 2025, ACM (Association for Computing Machinery),
DOI: 10.1145/3705328.3748053.
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