Psychological factors such as personality, emotions, social connections, and decision
biases can significantly affect the outcome of a decision process. These factors are also …

Understanding user's behavior and their interactions with artificial-intelligent-based systems
is as important as analyzing the performance of the algorithms used in these systems. For …

Promoting recommender systems in real-world applications requires deep investigations
with emphasis on their next generation. This survey offers a comprehensive and systematic …

Personalized recommender systems have become indispensable in today's online world.
Most of today's recommendation algorithms are data-driven and based on behavioral data …

In this technical survey, the latest advancements in the field of recommender systems are
comprehensively summarized. The objective of this study is to provide an overview of the …

Intelligence is the ability to learn from experience and use domain experts' knowledge to
adapt to new situations. In this context, an intelligent Recommender System should be able …

Recommender Systems have been developed for years to guide the interaction of the users
with systems in very diverse domains where information overload exists aimed to help …

Recommender systems have already proved to be valuable for coping with the information
overload problem in several application domains. They provide people with suggestions for …

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 …

The World Wide Web is a great source of products and services available to people.
Scientists have made a huge effort to create effective strategies to personalize those …