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"...How can recommendation engines best fulfill these needs?
Content recommendation solutions are usually classified with technical criteria depending on how they work under the hood. Without going into the details these include approaches like Semantic Analysis, where the recommendation engine uses the information contained in the content metadata to create clusters of similar or related programs.
Collaborative Filtering is the technique Amazon has made commonplace with the “people who like what you like also like this” feature. Other distinguishing features include a declarative approach where the recommendation system uses information that the viewer gave willingly, i.e. “I like action thrillers & sport but I don’t like romantic comedy”.
One of the trickiest techniques to implement in an IPTV setup is Behavior Analysis, where the system learns what you like more from what you actually watch than from what you say you like..."