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Erschienen in:
2015 | OriginalPaper | Buchkapitel
On the Influence of User Characteristics on Music Recommendation Algorithms
verfasst von : Markus Schedl, David Hauger, Katayoun Farrahi, Marko Tkalčič
Erschienen in: Advances in Information Retrieval
Verlag: Springer International Publishing
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We investigate a range of
music recommendation algorithm
combinations,
score aggregation functions
,
normalization techniques
, and
late fusion techniques
on approximately 200 million listening events collected through
Last.fm
. The overall goal is to identify superior combinations for the task of artist recommendation. Hypothesizing that user characteristics influence performance on these algorithmic combinations, we consider specific user groups determined by age, gender, country, and preferred genre. Overall, we find that the performance of music recommendation algorithms highly depends on user characteristics.