uchoice-Lastfm-Genres dataset
This is a universal subset choice dataset, so it
consists of a collection of subsets that are chosen from some
universal set of items. This dataset comes from the listening behavior
of users from the music streaming
service Last.fm. We break user
behavior into sessions, where a new session is created if the user
goes 20 minutes without starting a new song. We create subset choices
by the genres of music played in the session, where genres are derived
from user-provided tags for artists. We assign an artist to the most
commonly provided tag for that artist. Many subset selections contain
repeated genres, corresponding to cases when a user listens to the
same genre more than once in a session. This dataset was derived from
data
here
and
here.
Some basic statistics of this dataset are:
- number of items: 413
- number of subset selections: 643,982
- A Discrete Choice Model for Subset Selection.
Austin R. Benson, Ravi Kumar, and Andrew Tomkins.
In Proceedings of the 11th ACM International Conference on Web Search and Data Mining (WSDM), 2018. [bibtex] - Music Recommendation and Discovery in the Long Tail.
Òscar Celma.
Springer, 2010. [bibtex] - LastFM-ArtistTags2007 dataset.
Paul Lamere, 2008. [bibtex]