Case-based sequential ordering of songs for playlist recommendation

Authors:
Claudio Baccigalupo;Enric Plaza
Affiliations:
IIIA – Artificial Intelligence Research Institute, CSIC – Spanish Council for Scientific Research, Bellaterra, Catalonia, Spain;IIIA – Artificial Intelligence Research Institute, CSIC – Spanish Council for Scientific Research, Bellaterra, Catalonia, Spain
Venue:
ECCBR'06 Proceedings of the 8th European conference on Advances in Case-Based Reasoning
Year:
2006

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Abstract

We present a CBR approach to musical playlist recommendation. A good playlist is not merely a bunch of songs, but a selected collection of songs, arranged in a meaningful sequence, e.g. a good DJ creates good playlists. Our CBR approach focuses on recommending new and meaningful playlists, i.e. selecting a collection of songs that are arranged in a meaningful sequence. In the proposed approach, the Case Base is formed by a large collection of playlists, previously compiled by human listeners. The CBR system first retrieves from the Case Base the most relevant playlists, then combines them to generate a new playlist, both relevant to the input song and meaningfully ordered. Some experiments with different trade-offs between the diversity and the popularity of songs in playlists are analysed and discussed.