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From Niall Riddell <niall.ridd...@xspca.com>
Subject Re: Need some pointers towards algorithm capabilities.
Date Thu, 16 Dec 2010 10:38:34 GMT
I recommend buying Mahout in Action.  It's a Manning Early Access Program
publication.

Sean Owen has been helping me work through some of the code examples.

Cheers Niall

On 16 December 2010 10:35, Niels Basjes <Niels@basjes.nl> wrote:

> Hi,
>
> I'm an experienced developer yet a complete newbie when it comes to
> the type of functionality Mahout offers.
> I do have some experience in designing and writing MapReduce jobs in
> Hadoop so I understand enough of the base platform that is used.
>
> I want to investigate and experiment with both the item-item and
> user-item recommenders in Mahout.
> The problem I have is that I'm having a hard time finding a good
> overview of the capabilities of the various algorithms.
> Most Wikipedia articles immediately dive into the underlying
> mathematical foundations instead of the practical implications I'm
> looking for.
> I've also not been able to find what I'm looking for in the Mahout
> Wiki/Confluence.
>
> Putting it simply I'm looking for a comprehensive overview of
> - the kind of things you can and cannot do with the various algorithms
> that are available in Mahout.
>    - can it handle both "Implicit" and "Explicit" ratings.
>    - can I 'age' the relevance of the (implicit) ratings? I.e.
> Recommendations should change with the changing taste.
>    - how does it handle in long tail situations (with millions of
> items most are only viewed/rated very infrequently)
> - what are the scaling properties of the algorithms.
>    - is it always batch or can I do real-time incremental updates
> with new ratings?
>    - can I preprocess a daily dataset and then combine the daily sets
> into "what I need"?
>
> Thanks for any info you can point me to.
>
> --
> Best regards,
>
> Niels Basjes
>



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Niall Riddell
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