Content based filtering

•Content based filtering recommends items based on a comparison between the content of the two items and a user profile. Each item is represented as a set of descriptors or terms which is usually the words or keywords.

•The user profile is represented with the same terms and built up by analysing the content of items which have been seen by the user.

•Several issues have to be considered when implementing this system. First, terms can either be assigned automatically or manually. When terms are assigned automatically a method has to be chosen that can extract these terms from items.

•Second, the terms have to be represented such that both the user profile and the items can be compared in a meaningful way.

•Third, a learning algorithm has to be chosen that is able to learn the user profile based on seen items and can make recommendations based on this user profile.