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? >