Summary

In this chapter, we learned what recommendation engines are and how they are important to businesses as well as what value they provide to the customer. We discussed association rule mining and market basket analysis and how this simple method is being used in the industry. Then we went through content-based filtering and its advantages and disadvantages. We then discussed collaborative filtering and different types of collaborative filtering, namely user-based and item-based collaborative filtering. The aim of user-based collaborative filtering is finding similar users that have past ratings or behavior somewhat similar to the target user, whereas item-based collaborative filtering looks for patterns in ratings of items to find like-minded users and to recommend items.