Smart farming aims to improve farming using modern technologies and smart devices. Smart
devices help farmers to collect and analyze data regarding different aspects of their …

Collaborative filtering recommender systems (CFRSs) have already been proved effective to
cope with the information overload problem since they merged in the past two decades …

Recommender systems are a promising way for users to quickly find the valuable
information that they are interested in from massive data. Concretely, by capturing the user's …

With the ever‐increasing popularity of mobile computing technology, a wide range of
computational resources or services (eg, movies, food, and places of interest) are migrating …

Data sparsity is a widespread problem of collaborative filtering (CF) recommendation
algorithms. However, some common CF methods cannot adequately utilize all user rating …

With the advance of mobile edge computing (MEC), the number of edge services running on
mobile devices grows explosively. In this situation, it is becoming a necessity to recommend …

With the advent of Internet of Things (IoT) age, the variety and volume of web services have
been increasing at a fast speed. This often leads to users' selections for web services more …

A large amount of data and applications need to be shared with various parties and
stakeholders in the cloud environment for storage, computation, and data utilization. Since a …

Integrating lightweight web application programming interfaces (APIs) into mobile Apps is a
promising way for quick and cost-effective development of mobile Apps with desired …

This paper proposes a novel model called Space Time Features-based Recurrent Neural
Network (STF-RNN) for predicting people next movement based on mobility patterns …