Recommendation Systems and Netflix Prize

Spring 2007

CSE 4403-06 (CRN: 13574) Independent Study
CSE 5801-06 (CRN: ?) Independent Research

Philip Chan
242 Engineering Complex, 674-7280

Office Hours: MW 1-3pm (or by appointment)
Course WWW Page:

To improve customer experience, Netflix, an online DVD rental company, tries to recommend relevant movies to its customers. Netflix and's recommendation systems, according to some sources, are among the most sophisticated in the world. On Oct 2, 2006, Netflix announced the Netflix Prize and challenged the world, with a $1 million award, to devise an algorithm that can acheive a 10% improvement in accuracy over its current algorithm within 5 years. The data set for the competition contains about 1GB of data (which is only a subset of the whole data set) and Netflix' algorithm usually takes days to train its recommendation system. The entry from the most accurate contestant so far has made about 6.5% improvement. Hence, the problem is large as well as difficult. We are going to study some of the research papers in recommendation systems and devise algorithms to enter the competition.

Term paper

Prerequisites for CSE 4403 (undergraduate students)

Prerequisites for CSE 5801 (graduate students)


Philip Chan
Last modified: Fri Jan 5 14:18:45 EST 2007