We will be using a very specific data model for our recommender system, which is based on the dataset that we imported in the previous chapter. All we have changed is that we added a couple of products and brands to the model, and inserted some data into the database correspondingly. In total, we added the following:
- Ten products
- Three product brands
- Fifty relationships between existing person nodes and the mentioned products, highlighting that these persons bought these products
These are the products and brands that we added:
Adding products and brands to the dataset
The following diagram shows the resulting model:
In Neo4j, that model will look something like the following:
A graph model for our recommender model
A dataset like this one, while of course a broad simplification, offers us some interesting possibilities for a recommender system. Let's take a look at some queries that could really match this use case, and that would allow us to either visually or in real time exploit the data in this dataset in a product recommendation application.