On the Internet, where the number of choices is overwhelming, there is need to filter,
prioritize and efficiently deliver relevant information in order to alleviate the problem of …

Adaptive web sites may offer automated recommendations generated through any number
of well-studied techniques including collaborative, content-based and knowledge-based …

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

The design of algorithms that generate personalized ranked item lists is a central topic of
research in the field of recommender systems. In the past few years, in particular …

Publicly accessible adaptive systems such as collaborative recommender systems present a
security problem. Attackers, who cannot be readily distinguished from ordinary users, may …

The Web has moved, slowly but steadily, from a collection of documents towards a collection
of structured data. Knowledge graphs have then emerged as a way of representing the …

In this chapter we provide a comprehensive overview of the topic of Intelligent Techniques
for Web Personalization. Web Personalization is viewed as an application of data mining …

Recommender systems are effectively used as a personalized information filtering
technology to automatically predict and identify a set of interesting items on behalf of users …

The advent of the Linked Open Data (LOD) initiative gave birth to a variety of open
knowledge bases freely accessible on the Web. They provide a valuable source of …

In most real-world scenarios, the ultimate goal of recommender system applications is to
suggest a short ranked list of items, namely top-N recommendations, that will appeal to the …