Monday, June 29, 2009

After Netflix

Well - a (combined) team has finally managed to get to the finishing line - many,many congratulations to them. I must admit I feel a mix of regret not to be slightly further up the leaderboard and relief that I can now (bar a few desperate throws of the dice) concentrate on taking the learnings from Netflix elsewhere.

The competition has been very good to me, and I'm now engaged on a variety of projects trying to leverage the skills learnt including:

  • Producing a film and television recommendation system http://marketingfeeds.nl/TechCrunch/2009/06/03/beeTV_Raises_$8_Million_For_Stunning_Personal_TV_Recommendation_System
  • Working for a number of dating agencies http://www.onlinepersonalswatch.com/news/2009/04/gavin-potter-and-nick-tsinonis-founders-of-intro-analytics.html trying to help them identify compatible people - the interesting twist here is that as well as the person having to like the movie the movie has to like the person as well - if you see what I mean)
  • Identifying who might have to go to the accident and emergency department of a hospital so that careplans can be put in place to reduce the likelihood of an emergency admission thereby reducing costs and improving patient satisfaction. (the movie equivalent here is the treatments they received in the last year).
  • Working on a project to predict the prices of ... (I'm afraid I can't talk about this one just yet).
The interesting thing is, that in all these cases, the application of the Netflix algorithms makes a substantial improvement over the status quo - I think the learnings from the Netflix competition have enormous applications both within recommendation systems and elsewhere. Hats off to Netflix for producing such a valuable advance in both the science (and probably more importantly) the number of people who can now tackle these kinds of problem.

If any of the Netflix contestants are interested in working on "real problems" please don't hesitate to get in touch. I've more work than I can handle at the moment.

4 comments:

Larry said...

Sounds like it was a lot of fun. I can try to help if I have the time. What kind of assistance are you looking for?

gael.vanderschelden said...

If you could predict books a like from my Librarything profile, it would be just great!

Michael said...

Interesting list of human problems which can be solved with variants of data analysis. At MediaUnbound, we think the Netflix Prize has been a nice occasion to bring up some of the central issues with recommendation technology systems.

Check out our series on underlying issues and assumptions in the Netflix contest here.

Absalon said...

Well played Gavin.

You personally got a lot of very positive publicity.