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From Ted Dunning <ted.dunn...@gmail.com>
Subject Re: Need for a distributed SVDRecommender
Date Fri, 19 Nov 2010 22:32:08 GMT
On Fri, Nov 19, 2010 at 2:27 PM, Sebastian Schelter <ssc@apache.org> wrote:

> Can I use the new LanczosSolver to
> >> achieve this?
>
> The paper "Large-scale Parallel Collaborative Filtering for the Netflix
> Prize" says that you can't use Lanczos to factorize a rating matrix as
> it is only partially specified. However someone with more mathematical
> expertise than me should validate that statement, hope I didn't get that
> wrong :)
>

You correctly quoted the statement.  But I don't think that the statement is
entirely
correct.  The difference in practice isn't all that big a deal.


> Ted is working on LatentFactorLogLinear models in MAHOUT-525 which can
> be used for recommendations too and should be superior to the approach
> of MAHOUT-542. They're not distributed but in the paper in which they
> are described the authors state that they could train the 1M Movielens
> Dataset in 7 minutes so they should be fast enough for your testcase.
>

This is where I would push for recommendations.  I have a preliminary
implementation
available on github, but I don't think it is ready to commit.  It does do
roughly what it
is supposed to do (on one test) but I don't have enough runtime with it to
have any
level of confidence yet.

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