LabelGen: An Anomaly Label Generative Framework for Enhanced Graph Anomaly Detection

journal contribution

posted on 2024-09-30, 00:21 authored by Siqi Xia, Sutharshan RajasegararSutharshan Rajasegarar, Lei PanLei Pan, Christopher Leckie, Sarah M Erfani, Jeffrey Chan

LabelGen: An Anomaly Label Generative Framework for Enhanced Graph Anomaly Detection

History

Journal

IEEE Access

Volume

12

Pagination

121971-121982

Location

Piscataway, N.J.

Publisher DOI

https://doi.org/10.1109/access.2024.3453178

Open access

Yes

ISSN

2169-3536

eISSN

2169-3536

Language

en

Publication classification

C1.1 Refereed article in a scholarly journal

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Publication URL

http://dx.doi.org/10.1109/access.2024.3453178

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Keywords

Anomalies in graphs generative adversarial networks k-hop neighborhood sampling deep learning Technology

Licence

CC BY-NC-ND 4.0

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