Ah well, if you have a priori user-user similarity, you can do
user-based recommendation for your new user even with no user-item
links for him/her. As long as you know user-user similarities you're
OK.

Ted's suggestion is essentially a variant of this. You could use
TreeClusteringRecommender to do what he says.

Your second question is a bit different from a question of
recommendation. Perhaps you would base such a list on *recent*
popularity? or recent positive change in popularity? You could
populate it with things that used to be popular?

On Tue, Apr 20, 2010 at 9:25 PM, Tolga Oral <tolga.o...@gmail.com> wrote:
> PlusAnonymousUserDataModel will work once the user clicks on couple items on
> the site, however still doesnt solve the dead-start problem. We are creating
> user similarities based on different attributes and use the similarities to
> recommend items (doesn't solve all cases though)
>
> However I am still interested in figuring out the most popular items with
> some diversity (otherwise new "interesting/good" items have no chance of
> ever getting in recommendations) ? Any ideas how we can do this in mahout?
>

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