Too Long; Didn't Read
A cold start problem is when the system cannot draw any inferences for users or items about which it has not yet gathered sufficient information. The problem is that in both cases we don’t have any history to base the recommendations on. This is a common problem of not being able to start recommending things. There are several ways of making recommendations without any historical data about the user or item. These methods involve using some sort of easily calculable algorithm of serving recommendations to users. The most common techniques are listed below.