2 citations · 2 across the 2 of their papers we have counts for
Showing cs.IRShow all
2 papers · 1 filter
cs.IR2024
On the challenges of studying bias in Recommender Systems: A UserKNN case study
Savvina Daniil, Manel Slokom, Mirjam Cuper +3
Statements on the propagation of bias by recommender systems are often hard to verify or falsify. Research on bias tends to draw from a small pool of publicly available datasets an…
cs.IR2022★ 2 cited
Hidden Author Bias in Book Recommendation
Savvina Daniil, Mirjam Cuper, Cynthia C. S. Liem +2
Collaborative filtering algorithms have the advantage of not requiring sensitive user or item information to provide recommendations. However, they still suffer from fairness relat…