Recommendation systems represent the methods that researchers originally developed to predict items that a user is most likely to be interested in. The ability of recommendation systems to give personalized suggestions on items makes them perhaps the most important technology in the context of the online purchasing world.
When used in e-commerce applications, recommendation engines uses sophisticated algorithms to improve the shopping experience for shoppers and allows service providers to customize products according to the preferences of the users.
In 2009, Netflix offered 1 million dollars to anyone who could provide an algorithm that could improve its existing recommendation engine (Cinematch) by more than 10%. The prize was won by BellKor's Pragmatic Chaos team.
