Using content-based filtering approaches, a series of discrete characteristics of an item is utilized to recommend additional items with similar properties. Sometimes it is based on a description of the item and a profile of the user's preferences. These approaches try to recommend items that are similar to those that a user liked in the past or is using currently.
A key issue with content-based filtering is whether the system is able to learn user preferences from users' actions regarding one content source and use them across other content types. When this type of RE is deployed, it can be used to predict items or ratings for items that the user is interested in.
