We will take a look at so-called recommender systems in this chapter. Such systems, broadly speaking, consist of two elementary parts:
A pattern discovery system: This is the system that somehow figures out what would be a useful recommendation for a particular target group. This discovery can be done in many different ways, but in general we see three ways to do so:
A business expert who thoroughly understands the domain of the graph database application will use this understanding to determine useful recommendations. For example, the supervisor of a "do-it-yourself" retail outlet would understand a particular pattern. Suppose that if someone came in to buy multiple pots of paint, they would probably also benefit from getting a gentle recommendation for a promotion of high-end brushes. The store has that promotion going on right then, so the recommendation would be very timely. This process would be a discovery process where the pattern that the business expert...
