Recommender systems are effective tools of information filtering that are prevalent due to
increasing access to the Internet, personalization trends, and changing habits of computer …

Recommender systems represent user preferences for the purpose of suggesting items to
purchase or examine. They have become fundamental applications in electronic commerce …

“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 …

Recommender systems have developed in parallel with the web. They were initially based
on demographic, content-based and collaborative filtering. Currently, these systems are …

A current focus of intense research in pattern classification is the combination of several
classifier systems, which can be built following either the same or different models and/or …

This paper presents an overview of the field of recommender systems and describes the
current generation of recommendation methods that are usually classified into the following …

Most recommender systems use Collaborative Filtering or Content-based methods to predict
new items of interest for a user. While both methods have their own advantages, individually …

The article presents a multidimensional (MD) approach to recommender systems that can
provide recommendations based on additional contextual information besides the typical …

With the growth of online information, varying personalization drifts and volatile behaviors of
internet users, recommender systems are effective tools for information filtering to overcome …

Purpose This paper aims to identify, evaluate and integrate the findings of all relevant and
high-quality individual studies addressing one or more research questions about …