# [2019.10.15] Cold-start for Users

I've never solved a user cold-start problem before. I mean, I worked
on an onboarding task. What to show to a new user for demonstrating
the most popular but also most diverse items. I solved a problem of
rating elicitation. I've never solved a problem of actual transfer
learning. When you have piles of data about users based on their
other activity, not directly related to your recommender system in
focus. Usually, you don't have such data and don't work in such a
scenario. First of all, it's difficult since frequently there are
quite many users. So you can't easily calculate a full similarity
matrix for them. That problem becomes intractable. And challenging!:)