In 2007, Netflix launched the second iteration of its annual competition where, for the grand prize of one million dollars, participants attempted to outperform the company’s movie recommendation system based on an anonymized dataset consisting of users’ viewing history and ratings. While the dataset was designed to protect users’ privacy, within a few weeks researchers at the University of Texas at Austin were able to re-identify a large number of users by combining the dataset with public ratings on websi
American Statistical Association