With the widespread use of Internet of things (IoT), mobile phones, connected devices and
artificial intelligence (AI), recommender systems (RSs) have become a booming technology …

Purpose This study explores privacy challenges in recommender systems (RSs) and how
they have leveraged privacy-preserving technology for risk mitigation. The study also …

In many online applications, the range of content that is offered to users is so wide that a
need for automated recommender systems arises. Such systems can provide a personalized …

The popularity of online recommender systems has soared; they are deployed in numerous
websites and gather tremendous amounts of user data that are necessary for …

Recommender systems enable merchants to assist customers in finding products that best
satisfy their needs. Unfortunately, current recommender systems suffer from various privacy …

The main goal of a personalized recommender system is to provide useful
recommendations on various items to the users. In order to generate recommendations, the …

Recommender systems (eg, Amazon. com) provide users with tailored products and
services, which have the potential to induce user privacy concerns. Although system …

Recommender systems (RS), serving at the forefront of Human-centered AI, are widely
deployed in almost every corner of the web and facilitate the human decision-making …

As one of the most successful AI-powered applications, recommender systems aim to help
people make appropriate decisions in an effective and efficient way, by providing …

Recommendation systems are crucially important for the delivery of personalized services to
users. With personalized recommendation services, users can enjoy a variety of targeted …