Incorporating user control into recommender systems based on naive bayesian classification
Verus Pronk, Wim Verhaegh, Adolf Proidl, Marco Tiemann · 2007
Recommender systems are increasingly being employed to personalize services, such as on the web, but also in electronics devices, such as personal video recorders. These recommenders learn a user profile, based on rating feedback from the user on, e.g., books, songs, or TV programs, and use machine learning techniques to infer the ratings of new items.