Online platforms in the Internet Economy commonly incorporate recommender systems that
recommend products (or “arms”) to users (or “agents”). A key challenge in this domain arises …

Recommender systems (RS) are used by many social networking applications and online e-
commercial services. Collaborative filtering (CF) is one of the most popular approaches …

Open data are gold mines because they can be used to create services that develop a smart
city while improving users' living conditions. Several research works go in this direction …

Fog computing is a new computing paradigm that extends cloud services by providing
computing resources in the form of fog nodes closer to the edge devices. Fog computing …

Popularity prediction has been studied in diverse online contexts with demonstrable
practical, sociological and technical benefit. Here, we add to the popularity prediction …

While recommendation plays an increasingly critical role in our living, study, work, and
entertainment, the recommendations we receive are often for irrelevant, duplicate, or …

Recommender systems aim to forecast users' rank, interests, and preferences in specific
products and recommend them to a user for purchase. Collaborative filtering is the most …

We present GeoSRS, a hybrid recommender system for a popular location-based social
network (LBSN), in which users are able to write short reviews on the places of interest they …

Recommender system plays a supporting role in the process of information filtering. It plays
a remarkable role in large-scale online shopping and product suggestions. This paper …

Recommender systems suggest items of interest to users based on their preferences. These
preferences are typically generated from user ratings of the items. If there are no ratings for a …