The content-based (also called content-filtering or cognitive) approach to recommendations described in chapter 4 creates profiles for users and items to characterize them. The profiles allow systems to match users with relevant items. The general principle of content-based methods is to identify the common characteristics of items that have received favorable feedback from a user (a positive rating, a purchase, a click) and then recommend to this user new items that share these characteristics. Content-based strategies require gathering information that might not be readily available, easy to collect, or directly relevant.