Skip to main content
Have a personal or library account? Click to login
Graflow: A Microservice Anomaly Detection Method Based on Cross-Modal Feature Fusion and Multi-Scale Graph Attention Networks Cover

Graflow: A Microservice Anomaly Detection Method Based on Cross-Modal Feature Fusion and Multi-Scale Graph Attention Networks

Journal of Artificial Intelligence and Soft Computing Research
Volume 16 (2026): Issue 4 (October 2026)
By: ,  ,  ,  ,   and    
Open Access
|Jun 2026
Authors

Authors

Shuangshi Zhao

Graduate School of Information and Communication, Ajou University, Gyeonggi-do, Republic of Korea

Kunming Liu

Graduate School of Information and Communication, Ajou University, Gyeonggi-do, Republic of Korea

Jianlin Lu

College of Information Science and Technology, Shihezi University, China

Zhejie Xu

College of Information Science and Technology, Shihezi University, China

Meifang Yan

School of Computer Science and Technology, Xinjiang Normal University, China

Keyuan Qiu

nightwish2024@163.com

College of Information Science and Technology, Shihezi University, China
DOI: https://doi.org/10.2478/jaiscr-2026-0017
Journal RSS Feed
Language: English
Page range: 343 - 366
Submitted on: Dec 11, 2025
Accepted on: May 11, 2026
Published on: Jun 29, 2026
Published by: SAN University
In partnership with: Paradigm Publishing Services
Keywords:
anomaly detection,
graph neural networks,
Microservice systems,
cross-modal fusion,
root cause localization
Related subjects:
Computer sciences,
Artificial intelligence,
Computer sciences,
Databases and data mining

© 2026 Shuangshi Zhao, Kunming Liu, Jianlin Lu, Zhejie Xu, Meifang Yan, Keyuan Qiu, published by SAN University
This work is licensed under the Creative Commons Attribution 4.0 License.

Volume 16 (2026): Issue 4 (October 2026)
Previous article
Next article