In the era of internet access, recommender systems try to alleviate the difficulty that
consumers face while trying to find items (eg, services, products, or information) that better …

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 …

Since their introduction in the early 1990's, automated recommender systems have
revolutionized the marketing and delivery of commerce and content by providing …

Due to the explosion of available information on the Internet, the need for effective means of
accessing and processing them has become vital for everyone. Recommender systems …

Recommender systems have become an important research field since the emergence of
the first paper on collaborative filtering in the mid-1990s. Although academic research on …

Recommender systems apply data mining techniques and prediction algorithms to predict
users' interest on information, products and services among the tremendous amount of …

Recommender Systems are used to mitigate the information overload problem in different
domains by providing personalized recommendations for particular users based on their …

Over the past two decades, a large amount of research effort has been devoted to
developing algorithms that generate recommendations. The resulting research progress has …

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

Recommender systems are typically provided as Web 2.0 services and are part of the range
of applications that give support to large-scale social networks, enabling on-line …