Recommender systems (RSs) have been playing an increasingly important role for informed
consumption, services, and decision-making in the overloaded information era and digitized …

Recommender systems have become a popular and effective means to manage the ever-
increasing amount of multimedia content available today and to help users discover …

For a long time, different recommendation tasks require designing task-specific architectures
and training objectives. As a result, it is hard to transfer the knowledge and representations …

In a variety of application domains the content to be recommended to users is associated
with text. This includes research papers, movies with associated plot summaries, news …

Factorization approaches provide high accuracy in several important prediction problems,
for example, recommender systems. However, applying factorization approaches to a new …

We propose to solve the link prediction problem in graphs using a supervised matrix
factorization approach. The model learns latent features from the topological structure of a …

In recent years, interest in recommender research has shifted from explicit feedback towards
implicit feedback data. A diversity of complex models has been proposed for a wide variety …