last.fm decay ratings

last.fm decay ratings

Citation Author(s):
Maria N
Moreno García
University of Salamanca
Submitted by:
Maria Moreno Garcia
Last updated:
Wed, 06/24/2020 - 02:52
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.

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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: Jul. 08, 2020.
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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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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