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From samsam <yangua...@gmail.com>
Subject Re: Recommend for anonymous users
Date Mon, 05 Jul 2010 15:32:11 GMT
About the second question,I have not the similarity,I want to know is how to
pre-compute the item similarity.

On Mon, Jul 5, 2010 at 11:20 PM, Sean Owen <srowen@gmail.com> wrote:

> 1) Good question. One answer is to make these "anonymous" users real
> users in your data model, at least temporarily. That is, they need not
> be anonymous to the recommender, even if they're not yet a registered
> user as far as your site is concerned.
>
> There's a class called PlusAnonymousUserDataModel that helps you do
> this. It wraps a DataModel and lets you quickly add a temporary user,
> recommend, then un-add that user. It may be the easiest thing to try.
>
> (BTW the book Mahout in Action covers this in section 5.4, in the
> current MEAP draft.)
>
> 2) Not sure I fully understand. You already have some external,
> pre-computed notion of item similarity? then just feed that in to
> GenericItemSimilarity and use it from there.
>
> Sean
>
> On Mon, Jul 5, 2010 at 1:52 PM, samsam <yanguango@gmail.com> wrote:
> > Hello,all
> > I want to build recommendation engine with apache mahout,I have read some
> > reading material,and I still have some questions.
> >
> > 1)How to recommend for anonymous users
> > I think recommendation engine  should return recommendations given a item
> > id.For example,a anonymous user reviews some items,
> > and tell the recommendation what he reviews,and compute with the reviews
> > histories.
> >
> > 2)How to compute the items similarity dataset
> > Without use items similarity dataset,we can make ItemBasedRecommender
> > with PearsonCorrelationSimilarity,but
> > we need to make recommendations with extra attributes of items,
> > so we should use the items similarity dataset,how to build the dataset is
> > the key point.
> > --
> > I'm samsam.
> >
>



-- 
I'm samsam.

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