3 citations · 5 across the 2 of their papers we have counts for
4 papers
Simulation as Experiment: An Empirical Critique of Simulation Research on Recommender Systems
Amy A. Winecoff, Matthew Sun, Eli Lucherini +1
Simulation can enable the study of recommender system (RS) evolution while circumventing many of the issues of empirical longitudinal studies; simulations are comparatively easier…
T-RECS: A Simulation Tool to Study the Societal Impact of Recommender Systems
Eli Lucherini, Matthew Sun, Amy Winecoff +1
Simulation has emerged as a popular method to study the long-term societal consequences of recommender systems. This approach allows researchers to specify their theoretical model…
Recommendation or Discrimination?: Quantifying Distribution Parity in Information Retrieval Systems
Rinat Khaziev, Bryce Casavant, Pearce Washabaugh +2
Information retrieval (IR) systems often leverage query data to suggest relevant items to users. This introduces the possibility of unfairness if the query (i.e., input) and the re…
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…