Recommender Systems for Fun and Profit

In October 2006, Netflix released 100 million movie ratings as part of a $1M prize for any team that could improve their movie recommendation system by more than 10%. This landmark data set generated intense interest from the statistics and machine learning communities, and attracted entries from over 3000 teams from academia and industry. In this talk, I will review AT&T's experience analyzing this data using collaborative filtering techniques, leading to our winning two $50,000 progress prizes, as well as a subsequent project applying the methodology to television viewing data.