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The Netflix prize, 300 days later
Read all about it, via Brad DeLong. I'll add a dose of Michael Polanyi to the debate and note that recommender systems work best when combined with non-articulable knowledge.
Posted by Tyler Cowen on July 31, 2007 at 01:27 PM in Economics | Permalink
Comments
It is pretty tough to create a good recommender system from a set of static data. But imagine you could change your recommendation system every hour, try it out on thousands of customers, and see what worked and what didn't.
Trying to solve the recommendation problem based on a dataset is thinking like an economist. A learning system with trial and error feedback is thinking like a computer programmer. ;-)
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