The accuracy of recommendations made by an online Recommender System (RS) is mostly
dependent on the underlying collaborative filtering algorithm. However, the ultimate …

Recommender systems provide advice to users about items they might wish to purchase or
examine. Recommendations made by such systems can help users navigate through large …

Academic research in the field of recommender systems mainly focuses on the problem of
maximizing the users' utility by trying to identify the most relevant items for each user …

Although algorithms have been widely used to deliver useful applications and services, it is
unclear how users actually experience and interact with algorithm-driven services. This …

Recommender systems are an important part of the information and e-commerce ecosystem.
They represent a powerful method for enabling users to filter through large information and …

Recommender systems use people's opinions about items in an information domain to help
people choose other items. These systems have succeeded in domains as diverse as …

Abstract Knowledge-based recommender technologies support customers and sales
representatives in the identification of appropriate products and services. These …

In a world where the number of choices can be overwhelming, recommender systems help
users find and evaluate items of interest. They connect users with items to …