Chapters 4 and 5 introduced two of the most common approaches to implementing recommendation engines: content-based and collaborative filtering. The advantages of each approach were highlighted, but several drawbacks also emerged during the discussion. Notably, these techniques require information about users that is not always available. This chapter covers another approach to recommendations that is useful when it is difficult or impossible to get access to user interaction history or other details about the users. In such cases, applying the classic approaches would not produce good results.
Suppose that you would like to build a recommendation engine for an online travel site. The site offers lodging reservations but doesn’t require login or registration in the early stages of the process. Using a session-based recommendation engine, it is possible to deliver recommendations even in cases like this one, in which little about the user is known.