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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Dataset Files

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[1] Maria N Moreno García, "last.fm decay ratings ", IEEE Dataport, 2020. [Online]. Available: http://dx.doi.org/10.21227/c21x-0534. Accessed: Mar. 02, 2021.
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doi = {10.21227/c21x-0534},
url = {http://dx.doi.org/10.21227/c21x-0534},
author = {Maria N Moreno García },
publisher = {IEEE Dataport},
title = {last.fm decay ratings },
year = {2020} }
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T1 - last.fm decay ratings
AU - Maria N Moreno García
PY - 2020
PB - IEEE Dataport
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Maria N Moreno García. (2020). last.fm decay ratings . IEEE Dataport. http://dx.doi.org/10.21227/c21x-0534
Maria N Moreno García, 2020. last.fm decay ratings . Available at: http://dx.doi.org/10.21227/c21x-0534.
Maria N Moreno García. (2020). "last.fm decay ratings ." Web.
1. Maria N Moreno García. last.fm decay ratings [Internet]. IEEE Dataport; 2020. Available from : http://dx.doi.org/10.21227/c21x-0534
Maria N Moreno García. "last.fm decay ratings ." doi: 10.21227/c21x-0534