There are three main types of Recommender systems.
Collaborative filtering – Collaborative filtering is a method of making automatic predictions by using the recommendations of other people. There are two types of collaborative filtering techniques –
- User-User collaborative filtering
- Item-Item collaborative filtering
Content-Based Filtering– Content-based filtering is based on the description of an item and a user’s choices. As the name suggests, it uses content (keywords) to describe the items, and the user profile is built to state the type of item this user likes.
Image – Collaborative filtering & Content-based filtering
Hybrid Recommendation Systems – Hybrid Recommendation engines are a combination of diverse rating and sorting algorithms. A hybrid recommendation engine can recommend a wide range of products to consumers as per their history and preferences with precision.