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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 12:10:26 GMT
I'm getting a little confused so let me clarify. You compute item-item
similarities using a *user-based* recommender actually. I understand
that part. In this first phase you treat items as users and item
features as items. Makes sense. Sounds like that is working.

Then we arrive at the real recommendation engine. You have tried an
item-based and user-based recommender. My first reaction is that you
should probably be using an item-based recommender, or else the
item-item similarities you computed are not used at all right?

Or did I misunderstand, and you are still talking about computing the
item-item similarity with a user-based versus item-based recommender.

I am not sure what you mean about using a user similarity metric in an
item-based recommender. No, that algorithm does not use any notion of
user similarity -- only item similarity. Which you precompute.

Moving data to a JDBC- or Lucene-backed data store won't change the
quality of recommendations, it will just change the memory and speed
characteristics.

On Mon, Jul 13, 2009 at 12:19 PM, Thomas Rewig<trewig@mufin.com> wrote:
> The UserBasedRecommender don't work for me! In comparative with the
> Itembased-Recommender the Recommendations of the Userbase-Recommender are
> really bad. Only/mostly popular Items will be recommended.
> I think this is because I had a lot of Items and a lot of Users - but the
> most Users occupied only a few Items and the overlap of Users is sparse. Now
> there are a few other Users which occupied a lot of Items and randomly own a
> Item of the User the recommendation is made for - so Items were be
> recommended that have nothing in common with the profile of the user.
>
> So I have to use a recommender which bases only on the Item-Item-Matrix and
> the Userprofile from the User the Recommendation is made for: The
> ItemBasedRecommender. But I compute my Item-Item-Matrix with a
> UserSimilarity. Is there a way to get a UserSimilarity in a
> Item-Based-Recommender? Cast it somehow - so that I could compute the
> Item-Item-Similarity "on the fly" like I do this now?
>
> Otherwise I would precompute the whole Item-Item-Matrix like I do it before
> and put the Data with Sean's brand new MySQLJDBCItemSimilarity in the
>  ItemBased - System. (I will test this now). Thank you for that!

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