Chapter 3. Recommender Systems

This chapter shows some popular recommendation techniques. In addition, we will implement some of them in R.

We will deal with the following techniques:

  • Collaborative filtering: This is the branch of techniques that we will explore in detail. The algorithms are based on information about similar users or similar items. The two sub-branches are as follows:
    • Item-based collaborative filtering: This recommends to a user the items that are most similar to the user's purchases
    • User-based collaborative filtering: This recommends to a user the items that are the most preferred by similar users
  • Content-based filtering: This is for each user; it defines a user profile and identify the items that match it.
  • Hybrid filtering: This ...

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