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From Sean Owen <sro...@gmail.com>
Subject Re: Memory and Speed Questions for Item-Based-Recommender
Date Mon, 13 Jul 2009 08:36:16 GMT
How does Lucene go from item-item links to recommendations? I'm
missing where the notion of user ratings, or even users, come into
play, or the strength of the association.

If the issue is really just storing the item-item links efficiently in
a way that isn't in memory, how about I cook up a JDBC-based
implementation? Seem more direct.

On Fri, Jul 10, 2009 at 11:56 PM, Ted Dunning<ted.dunning@gmail.com> wrote:
> Yes.
>
> One gotcha is that you generally have to limit document size a bit to get
> good performance.  This is not a big deal because document normalization
> makes it hard for these documents to be retrieved in any case.  Also, these
> are typically not good second order recommendations.  First order
> recommendations are the top-40 kinds of things and make poor recommendations
> for a bunch of reasons.  Second order recommendations are those that are
> based on your history.  They make much better recommendations.
>
> On Fri, Jul 10, 2009 at 3:50 PM, Jason Rutherglen <
> jason.rutherglen@gmail.com> wrote:
>
>> Interesting. So we're creating the item-item matrix using one of the Mahout
>> algorithms (like Taste?), then dumping it into Lucene.
>>
>

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