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 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 …

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 …

The goal of a Recommender System is to generate meaningful recommendations to a
collection of users for items or products that might interest them. Suggestions for books on …

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 …

When the Netflix Prize launched in 2006, it put a spotlight on the importance and use of
recommender systems in real-world applications. The competition provided many lessons …

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

We bring to the fore of the recommender system research community, an inconvenient truth
about the current state of understanding how recommender system algorithms and humans …

Recommender systems (RSs), as used by Netflix, YouTube, or Amazon, are one of the most
compelling success stories of AI. Enduring research activity in this area has led to a …

Recommender systems have the effect of guiding users in a personalized way to interesting
objects in a large space of possible options. Content-based recommendation systems try to …