Recently, recommender systems have played an increasingly important role in a wide
variety of commercial applications to help users find favourite products. Research in the …

Recommender system (RS) has emerged as a major research interest that aims to help
users to find items online by providing suggestions that closely match their interest. This …

A recommender system aims to provide users with personalized online product or service
recommendations to handle the increasing online information overload problem and …

A recommender system is a Web technology that proactively suggests items of interest to
users based on their objective behavior or explicitly stated preferences. Evaluations of …

Recommender systems arose in view of the information overload present in numerous
domains. The so-called content-based recommenders offer products similar to those the …

Behaviorism is the currently-dominant paradigm for building and evaluating recommender
systems. Both the operation and the evaluation of recommender system applications are …

Recommender systems are widely used to provide users with recommendations based on
their preferences. With the ever-growing volume of information online, recommender …

While online content is personalized to an increasing degree, eg. using recommender
systems (RS), the rationale behind personalization and how users can adjust it typically …

If we assume that an important function of recommender systems is to help people make
better choices, it follows that people who design and study recommender systems ought to …

Recommender systems are the algorithms which select, filter, and personalize content
across many of the world's largest platforms and apps. As such, their positive and negative …