User-based collaborative filtering (UBCF) is widely used in recommender systems (RSs) as
one of the most successful approaches, but traditional UBCF cannot provide …

Recommender system (RS) can produce personalized service to users by analyzing their
historical information. User-based collaborative filtering (UBCF) approach is widely utilized …

Recommender systems (RSs) provide personalized information by learning user
preferences. User-based collaborative filtering (UBCF) is a significant technique widely …

The recommender system (RS) can help us extract valuable data from a huge amount of raw
information. User-based collaborative filtering (UBCF) is widely employed in practical RSs …

Recommender systems provide personalized information by learning user preferences.
Collaborative filtering (CF) is a common technique widely used in recommendation systems …

Recommender systems, which provide users with recommendations of content suited to
their needs, have received great attention in today's online business world. However, most …

Recommender Systems (RS) aim at suggesting to users one or several items in which they
might have interest. These systems have to update themselves as users provide new …

Recommender systems (RS) analyze user rating information and recommend items that may
interest users. Item-based collaborative filtering (IBCF) is widely used in RSs. However …

Recommender system (RS) suggests relevant objects to generate personalized service and
minimize information overload issue. User-based collaborative filtering (UBCF) plays a …

Recommender systems suggest a few items from many possible choices to the users by
understanding their past behaviors. In these systems, the user behaviors are influenced by …