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From Jake Mannix <jake.man...@gmail.com>
Subject Re: To all the recommendation people..
Date Sun, 15 May 2011 04:11:56 GMT
It's actually a pretty interesting challenge, once you get past the
constrictions of
their API: you're optimizing explicitly for revenue-per-session, take as
input
past sessions, which include the kinds of practical things you'd like: each
session is by a userId which will naturally include repeat customers,
products
have prices, and there are categoryId labels already.

Due to the whole Netflix data lawsuit, the training data is synthetic, which
puts the contestants at a disadvantage, and another interesting fact:
runtime
performance is at issue: your code will be run *live*, with your model being
used to produce recommendations with a hard timeout of 50ms - if you
miss this more than 20% of the time, you fail to progress to the end of
the semi-final round.

You're allowed to use open-source Apache licensed code (and are in fact
*required* to license your code according to the ASL to compete), but
their APIs are, while extraordinarily similar to Hadoop and Mahout/Taste,
are fixed, so you can't just do drop-in replacement.

On Sat, May 14, 2011 at 6:45 PM, Grant Ingersoll <gsingers@apache.org>wrote:

> Ah, you are right.  Read too quickly.
>
> On May 14, 2011, at 6:32 PM, Jake Mannix wrote:
>
> > You're allowed to be an individual, or a team not associated with an
> > academic institution, according to what I'm reading on that page...
> >
> > On Sat, May 14, 2011 at 3:13 PM, Grant Ingersoll <gsingers@apache.org
> >wrote:
> >
> >> Ah, never mind.  Academics only.  :-(
> >>
> >>
> >> On May 14, 2011, at 5:34 PM, Danny Bickson wrote:
> >>
> >>> Another interesting collaborative filtering contest with a big prize of
> >> 1M $.
> >>> See http://overstockreclabprize.com/
> >>>
> >>> - Danny Bickson
> >>
> >>
> >>
>
>
>

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