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From Jake Mannix <jake.man...@gmail.com>
Subject Re: distributed SVD
Date Thu, 06 May 2010 19:20:19 GMT
Tamas,

  MAHOUT-371 will be able to leverage the existing DistributedLanczosSolver
and DistributedRowMatrix (in o.a.m.math.decomposer.hadoop package in core)
to do full sparse truncated SVD on the entire user-item matrix already, so
that part is taken care of.

  -jake

On Thu, May 6, 2010 at 11:38 AM, Tamas Jambor <jamborta@googlemail.com>wrote:

> that looks interesting, but quite general. I'd be interested to know how he
> plans to divide the task that will be distributed. I mean SVD in general
> takes the whole user-item matrix, so it will be challenging to find a good
> way to divide the task. Papers written on SVD do not discuss this aspect, as
> far as I know.
>
>
> On 06/05/2010 18:32, Sean Owen wrote:
>
>> We're lucky to have a GSoC student implementing this over the summer:
>> https://issues.apache.org/jira/browse/MAHOUT-371
>>
>> On Thu, May 6, 2010 at 6:28 PM, Tamas Jambor<jamborta@googlemail.com>
>>  wrote:
>>
>>
>>> I am looking into the problem of distributed SVD for recommender systems.
>>> does anyone know whether someone else tried to tackle this problem
>>> before?
>>>
>>>
>>>
>>

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