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 …

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 …

Research and development of recommender systems has been a vibrant field for over a
decade, having produced proven methods for “preference-aware” computing …

Recommender systems use the opinions of members of a community to help individuals in
that community identify the information or products most likely to be interesting to them 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 …

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 …

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 help users find information by recommending content that a user
might not know about, but will hopefully like. Rating-based collaborative filtering …

Collaborative filtering is a broad and powerful framework for building recommendation
systems that has seen widespread adoption. Over the past decade, the propensity of such …