One distinctive feature of any adaptive system is the user model that represents essential
information about each user. This chapter complements other chapters of this book in …

Searching for and making decisions about information is becoming increasingly difficult as
the amount of information and number of choices increases. Recommendation systems help …

Over the last five years, a range of projects have focused on progressively more elaborated
techniques for adaptive news delivery. However, the adaptation process in these systems …

Recommender systems are a special class of personalized systems that aim at predicting a
user's interest on available products and services by relying on previously rated items or …

This article proposes Hermes, a Semantic Web-based framework for building personalized
news services. It makes use of ontologies for knowledge representation, natural language …

The Semantic Web aims to extend the World Wide Web with a layer of semantic information,
so that it is understandable not only by humans, but also by computers. At its core, the …

Knowledge-based recommender technologies provide a couple of mechanisms for
improving the accessibility of product assortments for customers, eg, in situations where no …

Recommender applications support decision-making processes by hel** online
customers to identify products more effectively. Recommendation problems have a long …

ABSTRACT As the World Wide Web matures, it rapidly grows in both size and complexity. In
this expanding environment, the needs and interests of individual users become buried …

Maintainability is a desired property of software, and a variety of metrics have been
proposed for measuring it, focusing on different notions of complexity and code readability …