Recommender systems have been widely used in different application domains including
energy-preservation, e-commerce, healthcare, social media, etc. Such applications require …

The rapidly expanding field of big data analytics has started to play a pivotal role in the
evolution of healthcare practices and research. It has provided tools to accumulate, manage …

“Nature shows us only the tail of the lion. But I do not doubt that the lion belongs to it even
though he cannot at once reveal himself because of his enormous size.”–Albert Einstein The …

In this age of information overload, people use a variety of strategies to make choices about
what to buy, how to spend their leisure time, and even whom to date. Recommender …

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 …

The popularity of online recommender systems has soared; they are deployed in numerous
websites and gather tremendous amounts of user data that are necessary for …

In many online applications, the range of content that is offered to users is so wide that a
need for automated recommender systems arises. Such systems can provide a personalized …

Provision of personalized recommendations to users requires accurate modeling of their
interests and needs. This work proposes a general framework and specific methodologies …

A common approach to designing Recommender Systems (RS) consists of asking users to
explicitly rate items in order to collect feedback about their preferences. However, users …

Point-of-Interest (POI) recommendation has been extensively studied and successfully
applied in industry recently. However, most existing approaches build centralized models on …