With the rapid development of edge intelligence in wireless communication networks,
mobile-edge networks (MENs) have been broadly discussed in academia. Supported by …

Recommender systems (RS) are among the most widely used applications in data mining
and machine-learning technologies. These technologies recommend relevant products to …

High-dimensional and incomplete (HDI) data subject to the nonnegativity constraints are
commonly encountered in a big data-related application concerning the interactions among …

High-Dimensional and Incomplete (HDI) data are frequently encountered in various Big
Data-related applications. Despite its incompleteness, an HDI data repository contains rich …

The emergence of Location-based social networks (LBSNs) in recent years has boosted
improvements in Recommender Systems for a new and specific task: the recommendation of …

Researchers face millions of research papers on various digital libraries. Therefore, finding
relevant research work that meets the preferences of a researcher is a challenging task …

We study the problem of recommending relevant products to users in relatively resource-
scarce markets by leveraging data from similar, richer in resource auxiliary markets. We …

With the rapid growth of Location-Based Social Networks, personalized Points of Interest
(POIs) recommendation has become a critical task to help users explore their surroundings …

Abstract Recommender Systems (RSs) aim to model and predict the user preference while
interacting with items, such as Points of Interest (POIs). These systems face several …

Abstract Recently, Next Point-of-Interest (POI) Recommendation which proposes users for
their next visiting locations, has gained increasing attention. A timely and accurate next POI …