Adversarial learning for weakly-supervised social network alignment

C Li, S Wang, Y Wang, P Yu, Y Liang, Y Liu… - Proceedings of the AAAI …, 2019 - ojs.aaai.org
Nowadays, it is common for one natural person to join multiple social networks to enjoy
different kinds of services. Linking identical users across multiple social networks, also …

Network alignment

R Tang, Z Yong, S Jiang, X Chen, Y Liu, YC Zhang… - Physics Reports, 2025 - Elsevier
Complex networks are frequently employed to model physical or virtual complex systems.
When certain entities exist across multiple systems simultaneously, unveiling their …

Adversarial-enhanced hybrid graph network for user identity linkage

X Chen, X Song, G Peng, S Feng, L Nie - Proceedings of the 44th …, 2021 - dl.acm.org
In this work, we investigate the user identity linkage task across different social media
platforms based on heterogeneous multi-modal posts and social connections. This task is …

Adversarial attacks on deep graph matching

Z Zhang, Z Zhang, Y Zhou, Y Shen… - Advances in Neural …, 2020 - proceedings.neurips.cc
Despite achieving remarkable performance, deep graph learning models, such as node
classification and network embedding, suffer from harassment caused by small adversarial …

MAUIL: Multilevel attribute embedding for semisupervised user identity linkage

B Chen, X Chen - Information Sciences, 2022 - Elsevier
User identity linkage (UIL) across social networks has recently attracted an increasing
amount of attention due to its significant research challenges and practical value. Most of the …

Robust attributed graph alignment via joint structure learning and optimal transport

J Tang, W Zhang, J Li, K Zhao… - 2023 IEEE 39th …, 2023 - ieeexplore.ieee.org
Graph alignment, which aims at identifying corresponding entities across multiple networks,
has been widely applied in various domains. As the graphs to be aligned are usually …

Graph alignment with noisy supervision

S Pei, L Yu, G Yu, X Zhang - Proceedings of the ACM Web Conference …, 2022 - dl.acm.org
Recent years have witnessed increasing attention on the application of graph alignment to
on-Web tasks, such as knowledge graph integration and social network linking. Despite …

His-GAN: A histogram-based GAN model to improve data generation quality

W Li, W Ding, R Sadasivam, X Cui, P Chen - Neural Networks, 2019 - Elsevier
Abstract Generative Adversarial Network (GAN) has become an active research field due to
its capability to generate quality simulation data. However, two consistent distributions …

Deep adversarial network alignment

T Derr, H Karimi, X Liu, J Xu, J Tang - Proceedings of the 30th ACM …, 2021 - dl.acm.org
Network alignment, in general, seeks to discover the hidden underlying correspondence
between nodes across two (or more) networks when given their network structure. However …

Unsupervised Alignment of Hypergraphs with Different Scales

MT Do, K Shin - Proceedings of the 30th ACM SIGKDD Conference on …, 2024 - dl.acm.org
People usually interact in groups, and such groups may appear on different platforms. For
instance, people often create various group chats on messaging apps (eg, Facebook …