Probabilistic preference learning from incomplete rank data
Ranking data are ubiquitous: we rank items as citizens, as consumers, as scientists, and we are
collectively characterised, individually classified and recommended, based on estimates of
our preferences. Preference data occur when we express comparative opinions about a set of
items, by rating, ranking, pair comparing, liking, choosing or clicking, usually in an
incomplete and possibly...