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

journal contribution

posted on 2025-04-04, 00:38 authored by Siqi XiaSiqi Xia, Sutharshan RajasegararSutharshan Rajasegarar, Lei Pan, Christopher Leckie, Sarah M Erfani, Jeffrey Chan

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

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Related Materials

1.
DOI - Is version of https://doi.org/10.1109/access.2024.3453178

Location

Piscataway, N.J.

Open access

Yes

Language

en

Publication classification

C1 Refereed article in a scholarly journal

Journal

IEEE Access

Volume

12

Pagination

121971-121982

ISSN

2169-3536

eISSN

2169-3536

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Publication URL

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

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Categories

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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