Signal propagation in complex networks

P Ji, J Ye, Y Mu, W Lin, Y Tian, C Hens, M Perc, Y Tang… - Physics reports, 2023 - Elsevier
Signal propagation in complex networks drives epidemics, is responsible for information
going viral, promotes trust and facilitates moral behavior in social groups, enables the …

Two-stream graph convolutional network-incorporated latent feature analysis

F Bi, T He, Y Xie, X Luo - IEEE Transactions on Services …, 2023 - ieeexplore.ieee.org
Historical Quality-of-Service (QoS) data describing existing user-service invocations are vital
to understanding user behaviors and cloud service conditions. Collaborative Filtering (CF) …

How to Isolate Non-Public Networks in B5G: A Review

Q Sun, N Hui, Y Zhou, L Tian, J Zeng, X Ge - Applied Sciences, 2022 - mdpi.com
Featured Application B5G non-public networks will serve various vertical industries, which
are developing rapidly in the era of the Internet of Things. It is forecasted that eight key …

Effective model integration algorithm for improving link and sign prediction in complex networks

C Liu, S Yu, Y Huang, ZK Zhang - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Link and sign prediction in complex networks bring great help to decision-making and
recommender systems, such as in predicting potential relationships or relative status levels …

Self-attention enhanced auto-encoder for link weight prediction with graph compression

Z Liu, W Zuo, D Zhang, C Zhou - IEEE Transactions on Network …, 2023 - ieeexplore.ieee.org
Predicting unobservable or missing weights over links on various real-world networks is of
fundamental scientific significance in disparate disciplines like sociology, biology, and …

Network structural perturbation against interlayer link prediction

R Tang, S Jiang, X Chen, W Wang, W Wang - Knowledge-Based Systems, 2022 - Elsevier
Interlayer link prediction aims at matching the same entities across different layers of the
multiplex network. Existing studies attempt to predict more accurately, efficiently, or …

Line graph neural networks for link weight prediction

J Liang, C Pu, X Shu, Y Xia, C Xia - arXiv preprint arXiv:2309.15728, 2023 - arxiv.org
In real-world networks, predicting the weight (strength) of links is as crucial as predicting the
existence of the links themselves. Previous studies have primarily used shallow graph …

A Node-Collaboration-Informed Graph Convolutional Network for Highly Accurate Representation to Undirected Weighted Graph

Y Yuan, Y Wang, X Luo - IEEE Transactions on Neural …, 2024 - ieeexplore.ieee.org
An undirected weighted graph (UWG) is regularly adopted to portray the interactions among
a solo set of nodes from big data-connected applications such as the interactive confidence …

Method of network intrusion discovery based on convolutional long-short term memory network and implementation in VSS

Z Fan, Z Cao - IEEE Access, 2021 - ieeexplore.ieee.org
Network intrusion discovery aims to detect the network attacks and abnormal network
intrusion efficiently, that is an important protection implement in the field of cyber security …

Improved Message Mechanism-Based Cross-Domain Security Control Model in Mobile Terminals

Z Cao, Z Fan, B Chen, Z Cheng, S Xu… - International Journal of …, 2024 - igi-global.com
Dual-domain terminal with two built-in independent operating systems-Life Domain and
Work Domain, provides convenience for daily use and mobile office. However, the security …