Recommender systems (RSs) are software tools and techniques that provide suggestions
for items that are most likely of interest to a particular user. In this introductory chapter, we …

A recommender system aims to provide users with personalized online product or service
recommendations to handle the increasing online information overload problem and …

Abstract Recommender Systems (RSs) are software tools and techniques providing
suggestions for items to be of use to a user. In this introductory chapter we briefly discuss …

Recommender systems, which provide users with recommendations of content suited to
their needs, have received great attention in today's online business world. However, most …

Recommender systems (RSs) are programs that apply knowledge discovery techniques to
make personalized recommendations for user's information on the web. In online sharing …

Recommender systems (RSs) are effective technologies and tools used to deal with the
problems of information overload, and have been developed rapidly in nearly two decades …

The emergence of social networks and the vast amount of data that they contain about their
users make them a valuable source for personal information about users for recommender …

Recommender systems are being widely used to assist people in making decisions, for
example, recommending films to watch or books to buy. Despite its ubiquity, the problem of …

Collaborative filtering is an emerging technology to deal with information overload problem
guiding customers by offering recommendations on products of possible interest. Forming …

In the previous chapter we introduced the task of proactive data mining and sketched an
algorithmic framework for solving the task: first build a prediction model and then use it for …