Recommender systems are firmly established as a standard technology for assisting users
with their choices; however, little attention has been paid to the application of the user model …

Among scheduling algorithms of scientific workflows, the graph partitioning is a technique to
minimize data transfer between nodes or clusters. However, when the graph partitioning is …

Content personalization is a long-standing problem for online news services. In most
personalization approaches users of a news service are represented by topical interest …

In this tutorial, we present an overview of the personalization field and review different types
of personalization. We also discuss the general personalization process and position the …

In this paper histograms of user ratings for movies (1 \bigstar,..., 10 \bigstar) are analysed.
The evolving stabilised shapes of histograms follow the rule that all are either double-or …

This article describes an approach for incorporating externally specified aggregate ratings
information into certain types of recommender systems, including two types of collaborating …

This paper describes an approach for incorporating externally specified aggregate ratings
information into certain types of collaborative filtering (CF) methods. For a statistical model …

Data-driven assessments and adaptive feedback are becoming a cornerstone research in
educational data analytics and involve developing methods for exploring the unique types of …

Previous work on using external aggregate rating information showed that this information
can be incorporated in several different types of recommender systems and improves their …

Recommender systems became an important element of many web-based systems. The
general process about how recommender systems fulfil various user needs based on the …