M Si, Q Li - Artificial Intelligence Review, 2020 - Springer
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 …
L Qi, X Wang, X Xu, W Dou, S Li - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
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 …
W Gong, L Qi, Y Xu - Wireless Communications and Mobile …, 2018 - Wiley Online Library
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 …
J Deng, J Guo, Y Wang - Knowledge-Based Systems, 2019 - Elsevier
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 …
X Chi, C Yan, H Wang, W Rafique… - … : Practice and Experience, 2022 - Wiley Online Library
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 …
AK Singh, R Gupta - Multimedia Tools and Applications, 2022 - Springer
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 …
W Gong, W Zhang, M Bilal, Y Chen… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
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 …