A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf
.
Model-Based Learning from Preference Data
2018
Annual Review of Statistics and Its Application
Preference data occurs when assessors express comparative opinions about a set of items, by rating, ranking, pair comparing, liking or clicking. The purpose of preference learning is to (i) infer on the shared consensus preference of a group of users, sometimes called rank aggregation; or (ii) estimate for each user her individual ranking of the items, when the user indicates only incomplete preferences; this is an important part of recommender systems. We provide an overview of probabilistic
doi:10.1146/annurev-statistics-031017-100213
fatcat:vtykf5bp5zconbvy6mvwktqtby