recommendations for new users

[Matt Mitchell <go...@gmail.com>]

Hi,

Slowly prototyping a recommendation here. The system does not have
user accounts. Since the users on the system don't have accounts, I'm
struggling a bit with completely new users, and what to recommend
them. I do have information about the user, like what referring site
they came from (1 of n partner sites), the city they want to shop in,
and rating value of the product. I wonder if I could use this
information, to find the most similar existing user. Then use that
most similar user to generate recommendations? Anyone have tips for
dealing this this?

I'm not sure if Mahout supports finding most "similar user" based on
user attributes, if not, this should be a simple sql/where-like select
from the database.

- Matt

Re: recommendations for new users

[Sean Owen <sr...@gmail.com>]

Have a look at the PlusAnonymousUserDataModel, which is a bit of a
hack but a decent sort of solution for this case. It lets you
temporarily add a user to the system and then everything else works as
normal, so you can make recommendations to these new / temp users.

There isn't a way to inject anything but rating/pref information
directly, no. You can use this info in a Rescorer to influence
recommendations; this is not specific to the case of a new user. You
can also decide to make "recommendations" by a completely different
means for new users -- for example, some canned list of top-10 recs
that is appropriate for their city or referring site. That's
legitimate too in practice.

Yes you can also find most-similar users based on this info. You'd
have to write the similarity metric yourself. I assume this is also
not the metric you use in your real recommender. So maybe you could
use it to find the nearest 1 real user and sub in those
recommendations? or a neighborhood. You would have to rewrite a bit of
what a recommender does to go this way but it's not so hard.

No there is no content-based similarity metric; this is so domain specific.

On Wed, Jul 4, 2012 at 4:54 PM, Matt Mitchell <go...@gmail.com> wrote:
> Hi,
>
> Slowly prototyping a recommendation here. The system does not have
> user accounts. Since the users on the system don't have accounts, I'm
> struggling a bit with completely new users, and what to recommend
> them. I do have information about the user, like what referring site
> they came from (1 of n partner sites), the city they want to shop in,
> and rating value of the product. I wonder if I could use this
> information, to find the most similar existing user. Then use that
> most similar user to generate recommendations? Anyone have tips for
> dealing this this?
>
> I'm not sure if Mahout supports finding most "similar user" based on
> user attributes, if not, this should be a simple sql/where-like select
> from the database.
>
> - Matt