Data augmentation based multi-view contrastive learning graph anomaly detection
Graph anomaly detection is valuable in preventing harmful events such as financial fraud and network intrusion. Although contrast-based anomaly detection methods could effectively mine anomaly information based on the inconsistency of anomalous node instance pairs, avoiding the drawback of using sel...
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Main Authors: | LI Yifan, LI Jiayin, LIN Xingpeng, DAI Yuanfei, XU Li |
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Format: | Article |
Language: | English |
Published: |
POSTS&TELECOM PRESS Co., LTD
2024-10-01
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Series: | 网络与信息安全学报 |
Subjects: | |
Online Access: | http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2024075 |
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