Create a recommender system that will recommend new musical artists to a user based on their listening history. Suggesting different songs or musical artists to a user is important to many music streaming services, such as Pandora and Spotify. In addition, this type of recommender system could also be used as a means of suggesting TV shows or movies to a user (e.g., Netflix).
This data set contains profiles for around 150,000 real people The dataset lists the artists each person listens to, and a counter indicating how many times each user played each artist
The dataset is continually growing; at the time of writing (6 May 2005) Audioscrobbler is receiving around 2 million song submissions per day
We may produce additional/extended data dumps if anyone is interested in experimenting with the data.
Please let us know if you do anything useful with this data, we're always up for new ways to visualize it or analyse/cluster it etc :)
This data is made available under the following Creative Commons license: http://creativecommons.org/licenses/by-nc-sa/1.0/
user_artist_data.txt 3 columns: userid artistid playcount
artist_data.txt 2 columns: artistid artist_name
artist_alias.txt 2 columns: badid, goodid known incorrectly spelt artists and the correct artist id. you can correct errors in user_artist_data as you read it in using this file (we're not yet finished merging this data)
rj@audioscrobbler.com irc://irc.audioscrobbler.com/audioscrobbler