With gigantic growth of information worldwide and the significant rise of users, companies nowadays are analyzing the past behavior of users to build intelligent applications to provide recommendations and choices of interest in terms of Relevant Job postings, Movies of Interest, Suggested Videos, Friends, or People You May Know, and so on. A Recommender System provides information or items that are likely to be of interest to a user in an automated fashion.
In this chapter, we will build, evaluate, and optimize three different categories of recommender systems: Content-based Recommenders, Collaborative Filtering, and Hybrid Recommenders.
The following illustration is indicative of their relations:
This chapter provides recipes ...