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From Marko Ciric <ciric.ma...@gmail.com>
Subject Re: question on writing a customized item similiarity function
Date Fri, 30 Sep 2011 10:12:08 GMT
I guess you think about of having an item similarity algorithms that depends
on item features.
You only need to implement a new ItemSimilarity as Sean already said. This
way, you could
make content-based recommendations with non-distrbute Taste.
Also, make sure you really want to do this with Taste, as you can also use
Mahout clustering
algorithms for this.

On 3 September 2011 10:04, Sean Owen <srowen@gmail.com> wrote:

> If you are referring to the non-distributed similarity function, it is
> quite
> easy: implement UserSimilarity or ItemSimilarity and use that as your
> similarity function. How you implement is up to you. If you say more about
> what you need to do, maybe people can suggest the right logic.
>
> On Sat, Sep 3, 2011 at 2:26 AM, Walter Chang <weidezhang2007@gmail.com
> >wrote:
>
> > Hi,
> >
> > If an item has both user rating and item specific contents(category, item
> > description content) for example for product recommendation, how can i
> > customize the similarity function ? As far as I understand, the current
> > mahout similarity function is based on user rating only. Any one had
> > experience writing a custom item based similarity function ?
> >
> > Thanks a lot,
> >
> > Weide
> >
>



-- 
--
Marko Ćirić
ciric.marko@gmail.com

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