Deep Information Fusion-Driven POI Scheduling for Mobile Social Networks

Authors

Zhiwei Guo, Chongqing Technology and Business University, China
Keping Yu, Hosei University, Japan & RIKEN Center for Advanced Intelligence Project, Japan
Ali Kashif Bashir, Manchester Metropolitan University, United Kingdom, & the National University of Science and Technology (NUST)
Di Zhang, Zhengzhou University, China
Yasser D. Al-Otaibi, King Abdulaziz University, Saudi Arabia
Mohsen Guizani, Mohamed bin Zayed University of Artificial IntelligenceFollow

Document Type

Article

Publication Title

IEEE Network

Abstract

With the growing importance of green wireless communications, point-of-interest (POI) scheduling in the mobile social network (MSN) environment has become important in addressing the high demand for innovative scheduling solutions. To enhance feature expressions for the complicated structures in MSNs, this article explores a deep information, fusion-based POI scheduling system of the MSN environment via the implementation of an edge-cloud deep hybrid sensing (PS-MSN) framework. Cloud sensing modules utilize the explicit contextual real-time information for each user, while edge sensing modules detect the real-time implicit linkages among users. Based on these two types of modules, a deep representation scheme is embedded into the hybrid sensing framework to improve its feature expression abilities. As a result, this type of framework is able to integrate multisource information so that more fine-grained feature spaces are built. In this work, two groups of experiments are conducted on a real-world dataset to evaluate the efficiency, as well as stability, of the designed PS-MSN. Using three benchmark methods to make comparisons, the excellent overall performance of PS-MSN is properly verified. IEEE

First Page

1

Last Page

7

DOI

10.1109/MNET.102.2100394

Publication Date

8-8-2022

Keywords

Computational modeling, Feature extraction, Semantics, Sensors, Social networking (online), Training, Wireless sensor networks, Benchmarking, E-learning, Online systems, Scheduling, Semantic Web, Social networking (online), User profile, Wireless sensor networks

Comments

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Recommended Citation

Z. Guo, K. Yu, A. K. Bashir, D. Zhang, Y. D. Al-Otaibi and M. Guizani, "Deep Information Fusion-Driven POI Scheduling for Mobile Social Networks," in IEEE Network, doi: 10.1109/MNET.102.2100394.