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- W2895527213 abstract "Automated recommendations for next tracks to listen to or to include in a playlist are a common feature on modern music platforms. Correspondingly, a variety of algorithmic approaches for determining tracks to recommend have been proposed in academic research. The most sophisticated among them are often based on conceptually complex learning techniques which can also require substantial computational resources or special-purpose hardware like GPUs. Recent research, however, showed that conceptually more simple techniques, e.g., based on nearest-neighbor schemes, can represent a viable alternative to such techniques in practice." @default.
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- W2895527213 date "2018-10-02" @default.
- W2895527213 modified "2023-10-01" @default.
- W2895527213 title "Effective Nearest-Neighbor Music Recommendations" @default.
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- W2895527213 doi "https://doi.org/10.1145/3267471.3267474" @default.
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