Stochastic relational models (SRMs) [15] provide a rich family of choices for learning and predicting dyadic data between two sets of entities. The models generalize matrix factor...
As context is acknowledged as an important factor that can affect users’ preferences, many researchers have worked on improving the quality of recommender systems by utilizing ...
—Recommender systems apply machine learning techniques for filtering unseen information and can predict whether a user would like a given resource. There are three main types of...
Accurate prediction of customer preferences on products is the key to any recommender systems to realize its promised strategic values such as improved customer satisfaction and t...
—Active learning can actively select or construct examples to label to reduce the number of labeled examples needed for building accurate classifiers. However, previous works of...