last.fm decay ratings

Citation Author(s):
Maria N
Moreno García
University of Salamanca
Submitted by:
Maria Moreno Garcia
Last updated:
Thu, 07/09/2020 - 05:14
DOI:
10.21227/c21x-0534
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Abstract 

 

This dataset is addressed to build time-aware music recommender systems when evolution of user preferences is considered. It was built by processing the data collected by Oscar Celma (https://www.upf.edu/web/mtg/lastfm360k) from last.fm. It consists of more than 80,000 songs listened to by 50 users over a 2-year period, creating a collection of more than 420,000 timestamped plays.

 

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Instructions: 

This dataset is addressed to build time-aware music recommender systems that consider evolution of user preferences over time. The entire dataset was split into a training set containing the data corresponding to the first months and a test set including data from the last 2 months. More information in the Readme file.