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ANALYZING CERTAIN TEMPORAL DEPENDENCES IN NETFLIX DATA

Netflix (see http://www.netflix.com/), an American Internet-based movie rental company, uses data mining in their recommendation system. In October 2006 Netflix made a huge data base of their users and movie evaluations available to the community and announced a million dollars prize to the team that beats the accuracy of their recommen- dations by at least 10%. The data have since become an object of interest of the machine learning community. In this paper, we focus on one aspect of the data that, to our know- ledge, has been overlooked — their temporal dependences. We have looked at the impact of the day of the week, month of the year, length of membership, month from the start of Netflix, etc., on the average evaluation.