Types of recommendation engines
We can broadly classify recommendation engines into three main categories:
- Content-based recommendation engines: They focus on item attributes, matching the features of one product to another.
- Collaborative filtering engines: They predict preferences based on user behaviors.
- Hybrid recommendation engines: A blend of both worlds, these engines integrate the strengths of content-based and collaborative filtering methods to refine their suggestions.
Having established the categories, let’s start by diving into the details of these three types of recommendation engines one by one:
Content-based recommendation engines
Content-based recommendation engines operate on a straightforward principle: they recommend items that are like ones the user has previously engaged with. The crux of these systems lies in accurately measuring the likeness between items.
To illustrate, imagine the scenario depicted in Figure...
