Identifying users from their rating patterns
José Bento, Nadia Fawaz, Andrea Montanari, Stratis Ioannidis · 2011
This paper reports on our analysis of the 2011 CAMRa Challenge dataset (Track 2) for context-aware movie recommendation systems. The train dataset comprises 4 536 891 ratings provided by 171 670 users on 23 974 movies, as well as the household groupings of a subset of the users. The test dataset comprises 5 450 ratings for which the user label is missing, but the household label is provided. The challenge required to identify the user labels for the ratings in the test set.