Recommender systems have become an integral part of online services due to their ability to
help users locate specific information in a sea of data. However, existing studies show that …

Research on recommender systems (RSs) has traditionally focused on the design of
systems capable of suggesting items of interest for users. However, often the most important …

With the new era of the Internet, we have a large amount of data available in the form of
ratings, reviews, graphs, images, etc. However, still, people face difficulty in finding useful …

Many of today's online services provide personalized recommendations to their users. Such
recommendations are typically designed to serve certain user needs, eg, to quickly find …

Adversarial machine learning is the research field investigating vulnerabilities inherent to
machine learning systems' design and ways to defend against them. Recently …

Although artificial intelligence (AI) outperforms humans in many tasks, research suggests
some consumers are still averse to having AI perform tasks on their behalf. Informed by the …

Nowadays, due to the increasing amount of data, the use of recommender systems has
increased. Therefore, the quality of the recommendations for the users of these systems is …

Recommender systems are traditionally optimized to facilitate content discovery for
consumers by ranking items based on predicted relevance. As such, these systems often do …

In order to facilitate communication, wireless networks are built from a collection of nodes
that may be either static or dynamic. They are acquiring a lot of popularity in the area of …

The proliferation of attacks on On-line Social Networks (OSNs) has imposed particular
attention by providers and users. This has an even higher importance for Social Reviewing …