Among collaborative recommendation approaches, methods based on nearest-neighbors
still enjoy a huge amount of popularity, due to their simplicity, their efficiency, and their ability …

Among collaborative recommendation approaches, methods based on nearest-neighbors
still enjoy a huge amount of popularity, due to their simplicity, their efficiency, and their ability …

“Nature shows us only the tail of the lion. But I do not doubt that the lion belongs to it even
though he cannot at once reveal himself because of his enormous size.”–Albert Einstein The …

Session-based recommendation is the task of predicting the next item to recommend when
the only available information consists of anonymous behavior sequences. Previous …

The rise of e-commerce has not only given consumers more choice but has also caused
information overload. In order to quickly find favorite items from vast resources, users are …

Although Recommender Systems have been comprehensively analyzed in the past decade,
the study of social-based recommender systems just started. In this paper, aiming at …

Many tasks in computer vision involve assigning a label (such as disparity) to every pixel. A
common constraint is that the labels should vary smoothly almost everywhere while …

With increasing presence and adoption of Web services on the World Wide Web, Quality-of-
Service (QoS) is becoming important for describing nonfunctional characteristics of Web …

Data sparsity, scalability and prediction quality have been recognized as the three most
crucial challenges that every collaborative filtering algorithm or recommender system …

As an indispensable technique in the field of Information Filtering, Recommender System
has been well studied and developed both in academia and in industry recently. However …