A hybrid approach to implementing recommender system means designing the system so as to making use of several recommendation techniques such as for instance collaborative filtering techniques and content-based filtering, making predictions from the combined conclusions of the two. This can be done by unifying the two techniques, by adding features from one into the other or simply by running algorithms for both techniques separately and then combine the results in some way. The most common example of a hybrid-based recommender system is the one used by Netflix. While an environment like Netflix is well suited for a hybrid recommender system, it does not fit everywhere. Why Netflix is considered a hybrid system:
- Collaborative Filtering: Observing the watching and browsing habits of similar users.
- Content-Based Filtering: Observing users with equal preferences and how they rated certain movies.