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From "Ted Dunning (JIRA)" <>
Subject [jira] Commented: (MAHOUT-542) MapReduce implementation of ALS-WR
Date Tue, 15 Mar 2011 00:40:29 GMT


Ted Dunning commented on MAHOUT-542:


Keeping multiple versions in the computation is exactly what I had in mind.  Whether this
is useful or not depends on whether each version of U and M are smaller than the original.
 They certainly will be more efficient to read.  As such, reading them multiple times might
be a win.

Or not.  I haven't worked out the details and that is what really, really matters here.

> MapReduce implementation of ALS-WR
> ----------------------------------
>                 Key: MAHOUT-542
>                 URL:
>             Project: Mahout
>          Issue Type: New Feature
>          Components: Collaborative Filtering
>    Affects Versions: 0.5
>            Reporter: Sebastian Schelter
>            Assignee: Sebastian Schelter
>         Attachments: MAHOUT-452.patch, MAHOUT-542-2.patch, MAHOUT-542-3.patch, MAHOUT-542-4.patch,
MAHOUT-542-5.patch, MAHOUT-542-6.patch,
> As Mahout is currently lacking a distributed collaborative filtering algorithm that uses
matrix factorization, I spent some time reading through a couple of the Netflix papers and
stumbled upon the "Large-scale Parallel Collaborative Filtering for the Netflix Prize" available
> It describes a parallel algorithm that uses "Alternating-Least-Squares with Weighted-λ-Regularization"
to factorize the preference-matrix and gives some insights on how the authors distributed
the computation using Matlab.
> It seemed to me that this approach could also easily be parallelized using Map/Reduce,
so I sat down and created a prototype version. I'm not really sure I got the mathematical
details correct (they need some optimization anyway), but I wanna put up my prototype implementation
here per Yonik's law of patches.
> Maybe someone has the time and motivation to work a little on this with me. It would
be great if someone could validate the approach taken (I'm willing to help as the code might
not be intuitive to read) and could try to factorize some test data and give feedback then.

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