Recommender systems were first conceived to provide suggestions of interesting items to
users. The evolution of such systems provided an understanding that a recommender …

Since the introduction of their modern form 20 years ago, recommender systems have
proven a valuable tool for help users manage information overload. Two decades of …

Recommender systems are tools for interacting with large and complex information spaces.
They provide a personalized view of such spaces, prioritizing items likely to be of interest to …

Recommender systems are now popular both commercially and in the research community,
where many approaches have been suggested for providing recommendations. In many …

Recommender systems' evaluation is usually based on predictive accuracy and information
retrieval metrics, with better scores meaning recommendations are of higher quality …

A recommender system is a set of tools for information retrieval. It improves access and
proactively recommends items and services that match users' tastes by considering their …

The field of recommender systems has reached an important milestone in Fall 2009 when
the $1,000,000 Netflix Prize Competition has successfully completed its course. Since then …

The origins of modern recommender systems date back to the early 1990s when they were
mainly applied experimentally to personal email and information filtering. Today, 30 years …

Recommender systems support users by generating potentially interesting suggestions
about relevant products and information. The increasing attention towards such tools is …

Recommender systems addvalue to vast content resources by matching users with items of
interest. In recent years, immense progress has been made in recommendation techniques …