BOURNE: Bootstrapped Self-Supervised Learning Framework for Unified Graph Anomaly Detection-Reference-Cited by-同舟云学术

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BOURNE: Bootstrapped Self-Supervised Learning Framework for Unified Graph Anomaly Detection

Published:2024-05-13 Issue: Volume:29 Page:2820-2833
ISSN:
Container-title:2024 IEEE 40th International Conference on Data Engineering (ICDE)
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Author:

Liu Jie¹,He Mengting¹,Shang Xuequn¹,Shi Jieming²,Cui Bin³,Yin Hongzhi⁴

Affiliation:

1. School of Computer Science, Northwestern Polytechnical University,Xi'an,China

2. The Hong Kong Polytechnic University,Department of Computing,HongKong,China

3. School of Computer Science, Peking University,Beijing,China

4. School of Electrical Engineering & Computer Science, The University of Queensland,Brisbane,Australia

Funder

National Nature Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10597630/10597390/10597844.pdf?arnumber=10597844

Reference52 articles.

1. From anomaly detection to rumour detection using data streams of social platforms

2. Heterogeneous Hypergraph Embedding for Graph Classification

3. Traffic Incident Detection: A Trajectory-based Approach

4. Graph Neural Network for Fraud Detection via Spatial-temporal Attention

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