Deep-Distributed-Learning-Based POI Recommendation Under Mobile-Edge Networks-Reference-Cited by-同舟云学术

Deep-Distributed-Learning-Based POI Recommendation Under Mobile-Edge Networks

Published:2023-01-01 Issue:1 Volume:10 Page:303-317
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Guo Zhiwei¹^ORCID,Yu Keping²^ORCID,Kumar Neeraj³^ORCID,Wei Wei⁴^ORCID,Mumtaz Shahid⁵^ORCID,Guizani Mohsen⁶^ORCID

Affiliation:

1. Chongqing Key Laboratory of Intelligent Perception and BlockChain Technology, National Research Base of Intelligent Manufacturing Service, Chongqing Technology and Business University, Chongqing, China

2. School of Computer and Information Engineering, Bengbu University, Bengbu, China

3. Department of Computer Science and Engineering, Thapar Institute of Engineering, Patiala, India

4. School of Computer Science and Engineering, Xi’an University of Technology, Xi’an, China

5. Nottingham Trent University, Nottingham, U.K.

6. Machine Learning Department, Mohamed Bin Zayed University of Artificial Intelligence, Masdar, UAE

Funder

National Natural Science Foundation of China

Humanities and Social Science Research Project of the Ministry of Education

Science and Technology Research Program of Chongqing Municipal Education Commission

Key Program of CTBU

Japan Society for the Promotion of Science (JSPS) Grants-in-Aid for Scientific Research

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/6488907/9997152/09869716.pdf?arnumber=9869716

Reference43 articles.

1. Towards Privacy-preserving Incentive for Mobile Crowdsensing Under An Untrusted Platform

2. A Proof of Local Convergence for the Adam Optimizer

3. Perceptual Enhancement for Autonomous Vehicles: Restoring Visually Degraded Images for Context Prediction via Adversarial Training

4. Social Topic Modeling for Point-of-Interest Recommendation in Location-Based Social Networks

5. Where to go: An effective point-of-interest recommendation framework for heterogeneous social networks

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