An essential goal of recommendation systems is to provide users with accurate and
personalized recommendations that meet their preferences. With the rapid growth of IoT …

Recommender systems can help correlate information and recommend personalised
services to users as a general information filtering tool. However, contextual factors …

Recommender Systems (RSs) are a subclass of information filtering systems. RSs assist
users in choosing interesting items from an extensive collection of items. This article …

Cyber-Physical-Social Systems (CPSS) provide great value to our lives, but they also cause
data overload problems. Data-driven personalized recommendation service is one of the …

With the prevalence of online social networking sites (OSNs) and mobile devices, people
are increasingly reliant on a variety of OSNs for keeping in touch with family and friends, and …

Session-based recommendation anticipates the next potential interest of users based on
their previous anonymous interactions, which is a crucial and indispensable component of …

E‐commerce companies often use image advertising as a marketing approach to introduce
potential customers to the goods or services that the business offers. People's tastes are …

Today, recommender systems are used in many different businesses to find items of interest
to users. The use of these systems is widely found in online economic systems and social …

Abstract We define Location Category Inference (LCI) as a task of predicting the category of
a visited venue, such as bar, restaurant or university, given user location GPS coordinates …

Barriers to the delivery of journalistic content to suitable media outlets present difficulties to
both journalists and publishing houses. These may take the form of barriers to the …