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From Alan Gardner <gard...@pythian.com>
Subject Re: Query in Mahout
Date Fri, 21 Jun 2013 20:13:09 GMT
I believe it's less intensive than training the whole set and throwing away
data. As an example: if you have 25 items across five categories, you would
do 25^2 = 625 comparisons to train an item-item model for all items
regardless of category. If you  train only within categories, you train
5*(5^2) = 125 operations. I don't think it's possible to do recommendation
with less than O(n^2) complexity, so it's a safe bet that running many
smaller recommenders will be cheaper than one big one.


On Fri, Jun 21, 2013 at 4:02 PM, Mouthgalya Ganapathy <
Mouthgalya.Ganapathy@infor.com> wrote:

> Thanks Alan for the Reply!!
> if we have item based  recommender model for each product category
> wouldn't that be computationally intensive?
>
>
> -----Original Message-----
> From: Alan Gardner [mailto:gardner@pythian.com]
> Sent: Friday, June 21, 2013 3:49 PM
> To: user@mahout.apache.org
> Subject: Re: Query in Mahout
>
> If you're doing item-based recommendation, doesn't it make sense to use
> multiple recommenders, one per category? This should reduce your training
> time, instead of training on all items then throwing away most of your
> results.
>
> If it was user-based recommendation I could see the value in finding
> similar users across multiple categories, then paring down the
> recommendations afterwards.
>
>
> On Fri, Jun 21, 2013 at 3:42 PM, Mouthgalya Ganapathy <
> Mouthgalya.Ganapathy@infor.com> wrote:
>
> > Hi,
> > For item based recommendations in Mahout, is there a way to get
> > recommendations from a selected Product category?
> > For example:
> > Product category A: Product1, Product2, Product3 Product Category B:
> > Product4, Product5, Product6
> >
> > Recommendations for product 2 should be only from category A i.e.
> > Product
> > 1 and 3.So recommendations should be only within the product category.
> > Is this possible?
> >
> >
> > Thanks,
> > Mouthgalya
> >
>
>
>
> --
> Alan Gardner
> Solutions Architect - CTO Office
>
> gardner@pythian.com | LinkedIn:
> http://www.linkedin.com/profile/view?id=65508699 | @alanctgardner<
> https://twitter.com/alanctgardner>
> Tel: +1 613 565 8696 x1218
> Mobile: +1 613 897 5655
>
> --
>
>
> --
>
>
>
>


-- 
Alan Gardner
Solutions Architect - CTO Office

gardner@pythian.com | LinkedIn:
http://www.linkedin.com/profile/view?id=65508699 |
@alanctgardner<https://twitter.com/alanctgardner>
Tel: +1 613 565 8696 x1218
Mobile: +1 613 897 5655

-- 


--




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