Analyzing Item Popularity Bias of Music Recommender Systems: Are Different Genders Equally Affected?

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

Original language	English
Title of host publication	Proceedings of the 15th ACM Conference on Recommender Systems (RecSys 2021)
Number of pages	10
Publication status	Published - 2021

Fields of science

@inproceedings{5c0939230955413ea094d943af139026,

title = "Analyzing Item Popularity Bias of Music Recommender Systems: Are Different Genders Equally Affected?",

author = "Oleg Lesota and Alessandro Melchiorre and Navid Rekabsaz and Stefan Brandl and D. Kowald and Elisabeth Lex and Markus Schedl",

year = "2021",

language = "English",

booktitle = "Proceedings of the 15th ACM Conference on Recommender Systems (RecSys 2021)",