The thesis describes the recommendation systems with an emphasis on user perspective. By this presents both user perception of recommendation systems as well as systemic perception of users.
In the first part we present the importance and usefulness of recommendation systems. Knowing the history of the development of recommendation systems allow us to understand it's todays importance. Further we look at the problems in the operation in detail and realize the difference between the user perspective and system metrics.
In the second part we compare the functioning of the existing film recommendation systems Jinni, TasteKid, MovieLens, Criticker, Rotten Tomatoes, IMDb, Suggest Me Movie A Good Movie To Watch, Flixter and Metacritic. We perform comparison and example of accuracy testing based on RMSE and MAE metrics.
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