3 citations · 5 across the 2 of their papers we have counts for
2 papers
cs.IR2022★ 3 cited
Exploring Popularity Bias in Music Recommendation Models and Commercial Steaming Services
Douglas R. Turnbull, Sean McQuillan, Vera Crabtree +2
Popularity bias is the idea that a recommender system will unduly favor popular artists when recommending artists to users. As such, they may contribute to a winner-take-all market…
cs.IR2019★ 2 cited
Assessing Fashion Recommendations: A Multifaceted Offline Evaluation Approach
Jake Sherman, Chinmay Shukla, Rhonda Textor +2
Fashion is a unique domain for developing recommender systems (RS). Personalization is critical to fashion users. As a result, highly accurate recommendations are not sufficient un…