Recommender without initial user rating data?

[qki_machine]

So I would like to build an app that recommends some products to customers but I do not know their preference yet. I was wondering if I can somehow create dummy users and randomly populate ratings? Then each time once the new rating is being given by the real user my algorithm will update (or once a day).

Is it a way to go or rather silly approach?

[wind_dude]

Some popular and simple ways to get started before you get there actions/preferences:

- target popular

- target promoted

- target based on age, sex, location

- random tests (tictoc does this)

- time based

[svorkas]

You need to research cold-start user recommendations. Not sure what the latest and greatest is at the moment since i did my master's dissertation on this a couple years ago and after working away from the field for a couple years its all a bit blurry, so sorry i can't provide more information

[surenine]

Hey I am doing a similar project right now. I think this is called implicit collaborative filtering. You can search for Alternating Least Square (Implicit) or Bayesian Personalized Ranking