Abstract The Internet and World Wide Web have brought us into a world of endless
possibilities: interactive Web sites to experience, music to listen to, conversations to …

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 …

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 …

The importance of contextual information has been recognized by researchers and
practitioners in many disciplines, including e-commerce, personalization, information …

Recommender systems have been regarded as gaining a more significant role with the
emergence of the first research article on collaborative filtering (CF) in the mid-1990s. CF …

Recommender systems provide valuable support for users who are searching for products in
e-commerce environments. Research in the field long focused on rating-based algorithms …

Recommender systems suggest items by exploiting the interactions of the users with the
system (eg, the choice of the movies to recommend to a user is based on those she …

The paper reviews and classifies recent research in recommender systems both in the field
of Computer Science and Information Systems. The goal of this work is to identify existing …

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 …

Recommender systems are gaining widespread acceptance in e-commerce applications to
confront the ldquoinformation overloadrdquo problem. Providing justification to a …