New technologies are emerging at a fast pace without being properly analyzed in terms of
their social impact or adequately regulated by societies. One of the biggest potentially …

Recommender systems have been widely used in different application domains including
energy-preservation, e-commerce, healthcare, social media, etc. Such applications require …

Among other conceptualizations, smart cities have been defined as functional urban areas
articulated by the use of Information and Communication Technologies (ICT) and modern …

Marketing has changed fundamentally in the new millennium. At the same time, sustainable
marketing strategies have evolved to meet the challenges of environmental issues. In this …

In recent years, the textile and fashion industries have witnessed an enormous amount of
growth in fast fashion. On e-commerce platforms, where numerous choices are available, an …

Learners can interact and connect with one another in new ways thanks to social media.
This study employs two models to investigate the factors that contribute to students' …

Collaborative filtering is a technique that takes into account the common characteristics of
users and items in recommender systems. Matrix decompositions are one of the most used …

In this paper, we introduce new formal methods and provide empirical evidence to highlight
a unique safety concern prevalent in reinforcement learning (RL)-based recommendation …

Context-aware recommender systems dedicated to online social networks experienced
noticeable growth in the last few years. This has led to more research being done in this …

Today's internet is able to discover almost any product or piece of information. The large
amounts of unfiltered information returned by an internet query calls for filters able to …