Active Learning for Recommender Systems : Cuvillier : 9783954046928 : 22 Apr 2014 : Nowadays we are living in an era that is overloaded with information. Decision-making in this environment can sometimes become a nightmare. There are too many choices and we simply cannot explore them all. Therefore, it would be really helpful to have a system to help us to find the right choice. Such systems, which learn user preferences and provide personalized recommendations to them are called Recommender Systems. Evidently, the performance of recommender systems depends on the amount of information that users provide regarding items, most often in the form of ratings. This problem is amplified for new users because they have not provided any rating, which impacts negatively on the quality of generated recommendations. This problem is called new user problem or cold-start problem. A simple and effective way to overcome this problem, is by posing queries to new users so that they express their prefe