RecSys - ACM Recommender Systems. Netflix Prize. The Netflix Prize was an open competition for the best collaborative filtering algorithm to predict user ratings for films, based on previous ratings without any other information about the users or films, i.e. without the users or the films being identified except by numbers assigned for the contest.
The competition was held by Netflix, an online DVD-rental service, and was open to anyone not connected with Netflix (current and former employees, agents, close relatives of Netflix employees, etc.) or a resident of Cuba, Iran, Syria, North Korea, Burma or Sudan.[1] On 21 September 2009, the grand prize of US$1,000,000 was given to the BellKor's Pragmatic Chaos team which bested Netflix's own algorithm for predicting ratings by 10.06%.[2] Problem and data sets[edit] Netflix provided a training data set of 100,480,507 ratings that 480,189 users gave to 17,770 movies.
Each training rating is a quadruplet of the form <user, movie, date of grade, grade>.