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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