Graph Autoencoder Anomaly Detection for E-commerce Application by Contextual Integrating Contrast With Reconstruction and Complementarity - Université de technologie de Compiègne
Journal Articles IEEE Transactions on Consumer Electronics Year : 2024

Graph Autoencoder Anomaly Detection for E-commerce Application by Contextual Integrating Contrast With Reconstruction and Complementarity

Jinjie Wu
  • Function : Author
Fujian Normal University [Fujian]
Zhipeng Qiu
  • Function : Author
Fujian Normal University [Fujian]
Zhixia Zeng
  • Function : Author
Fujian Normal University [Fujian]
Ruliang Xiao
Fujian Normal University [Fujian]
Imad Rida
Biomécanique et Bioingénierie
Shi Zhang
  • Function : Author
Fujian Normal University [Fujian]

Domains

Computer Science [cs]

Imad Rida  : Connect in order to contact the contributor

https://utc.hal.science/hal-04403908

Submitted on : Thursday, January 18, 2024-5:22:46 PM

Last modification on : Sunday, January 21, 2024-3:41:41 AM

No file

Dates and versions

hal-04403908 , version 1 (18-01-2024)

Identifiers

Cite

Jinjie Wu, Zhipeng Qiu, Zhixia Zeng, Ruliang Xiao, Imad Rida, et al.. Graph Autoencoder Anomaly Detection for E-commerce Application by Contextual Integrating Contrast With Reconstruction and Complementarity. IEEE Transactions on Consumer Electronics, 2024, pp.1-1. ⟨10.1109/TCE.2024.3352186⟩. ⟨hal-04403908⟩

Export

BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite

Collections

CNRS UNIV-COMPIEGNE BMBI
19 View
0 Download

Altmetric

Share

More