2 papers
cs.IR2024
The MovieLens Beliefs Dataset: Collecting Pre-Choice Data for Online Recommender Systems
Guy Aridor, Duarte Goncalves, Ruoyan Kong +2
An increasingly important aspect of designing recommender systems involves considering how recommendations will influence consumer choices. This paper addresses this issue by intro…
cs.IR2018
Exploring Author Gender in Book Rating and Recommendation
Michael D. Ekstrand, Daniel Kluver
Collaborative filtering algorithms find useful patterns in rating and consumption data and exploit these patterns to guide users to good items. Many of the patterns in rating datas…