A contest set up by Netflix, which offered a $1 million prize to anyone who could significantly improve its movie recommendation system, ended on Sunday with two teams in a virtual dead heat, and no winner to be declared until September.
Contest Produces Innovation
But the contest, which began in October 2006, has already produced an impressive legacy. It has shaped careers, spawned at least one start-up company and inspired research papers. It has also changed conventional wisdom about the best way to build the automated systems that increasingly help people make online choices about movies, books, clothing, restaurants, news and other goods and services.
The Biggest Lesson
The biggest lesson learned, according to members of the two top teams, was the power of collaboration. It was not a single insight, algorithm or concept that allowed both teams to surpass the goal Netflix, the movie rental company, set nearly three years ago: to improve the movie recommendations made by its internal software by at least 10 percent, as measured by predicted versus actual one-through-five-star ratings by customers.
Formula for Success
Instead, they say, the formula for success was to bring together people with complementary skills and combine different methods of problem-solving. This became increasingly apparent as the contest evolved.
Mr. Volinsky’s team, BellKor’s Pragmatic Chaos, was the longtime front-runner and the first to surpass the 10 percent hurdle. It is actually a seven-person collection of other teams, and its members are statisticians, machine learning experts and computer engineers from the United States, Austria, Canada and Israel.
Read the entire story at this link:
Steve Lohr, Netflix Competitors Learn the Power of Teamwork, New York Times, 27 July 2009.
Dr Geoff Pound
Geoff can be contacted by email at geoffpound(at)gmail.com on Facebook and Twitter.