Netflix Prize: Was The Napoleon Dynamite Problem Solved?
I just gave a talk at work on “Recommender Systems and the Netflix Prize”, and included the two major popular articles about the prize in its final year or so. One was in Wired Magazine and one was in the New York Times., and each focused on one outstanding problem that the competitors faced. Wired looked at the quirkiness of users as they rate movies, and the NYT focused on the difficulty of predicting ratings for a handful of divisive movies.
Now that the contest is over we can answer the question, “were those problems solved?”
Let’s start with the Wired article. Entitled “This Psychologist Might Outsmart the Math Brains Competing for the Netflix Prize” [link] it interviewed Gavin Potter, aka “Just a guy in a garage”. Here’s the hook:
The computer scientists and statisticians at the top of the leaderboard have developed elaborate and carefully tuned algorithms for representing movie watchers by lists of numbers, from which their tastes in movies can be estimated by a formula. Which is fine, in Gavin Potter’s view — except people aren’t lists of numbers and don’t watch movies as if they were.
Potter is focusing on effects like the … Continue reading