Abstract Recommender Systems (RSs) are software tools and techniques providing
suggestions of relevant items to users. These systems have received increasing attention …

With the advent of new cable and satellite services, and the next generation of digital TV
systems, people are faced with an unprecedented level of program choice. This often means …

Personalized recommendation systems can help people to find interesting things and they
are widely used with the development of electronic commerce. Many recommendation …

Recommender systems are typically provided as Web 2.0 services and are part of the range
of applications that give support to large-scale social networks, enabling on-line …

This paper presents a metric to measure similarity between users, which is applicable in
collaborative filtering processes carried out in recommender systems. The proposed metric …

In the context of e-learning recommender systems, we propose that the users with greater
knowledge (for example, those who have obtained better results in various tests) have …

Collaborative filtering (CF), one of the most successful recommendation approaches,
continues to attract interest in both academia and industry. However, one key issue limiting …

Recommender systems play an important role in reducing the negative impact of information
overload on those websites where users have the possibility of voting for their preferences …

As the use of recommender systems becomes more consolidated on the Net, an increasing
need arises to develop some kind of evaluation framework for collaborative filtering …

It seems reasonable to think that there may be some items and some users in a
recommender system that could be highly significant in making recommendations. For …