Recommendation engines aim at showing users items of interest. What makes them different from search engines is the relevant content usually appears on a website without having been requested, and users don't have to build queries, as recommendation engines observe the users' actions and construct the queries for users without their knowledge.
Arguably, the most well-known example of a recommendation engine is www.amazon.com, which provides personalized recommendation in a number of ways. The following screenshot shows an example of Customers Who Bought This Item Also Bought. As you will see later on, this is an example of collaborative item-based recommendation, where items similar to a particular item are recommended:
In this section, we will introduce key concepts related to understanding and building recommendation engines.