On the Influence of User Characteristics on Music Recommendation Algorithms

Description

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.

Period	31 Mar 2015
Event title	37th European Conference on Information Retrieval
Event type	Conference
Location	AustriaShow on map