Collaborative Filtering and the Netflix Prize
Abstract
Recommendation systems, and specifically collaborative filtering, are fairly new
fields, which focus on automatically predicting how much a given user would value a
given item. As more and more aspects of society are entering the digital realm, the value
of such systems is increasing. Improvements to the underlying algorithms and concepts
are still being discovered, and further research is being encouraged. Notably, Netflix
recently issued a challenge to the collaborative filtering community, with a million-dollar
prize offered for whomever could produce a significant improvement over their existing
recommendation system. This paper explores the history of collaborative filtering, and
many of the core concepts and methods. In addition, the progress of the winning teams
from the Netflix Prize is tracked and their methods explored. Finally, there is a look
ahead at potential challenges that those working in the field of collaborative filtering will
have to overcome.