PLELog: Semi-Supervised Log-Based Anomaly Detection via Probabilistic Label Estimation-Reference-Cited by-同舟云学术

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PLELog: Semi-Supervised Log-Based Anomaly Detection via Probabilistic Label Estimation

Published:2021-05 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)
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Author:

Yang Lin,Chen Junjie,Wang Zan,Wang Weijing,Jiang Jiajun,Dong Xuyuan,Zhang Wenbin

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9402220/9402274/09402368.pdf?arnumber=9402368

Cited by 29 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Revisiting Log Parsing: The Present, the Future, and the Uncertainties;IEEE Transactions on Reliability;2024-09

2. ContexLog: Non-Parsing Log Anomaly Detection With All Information Preservation and Enhanced Contextual Representation;IEEE Transactions on Network and Service Management;2024-08

3. SaRLog: Semantic-Aware Robust Log Anomaly Detection via BERT-Augmented Contrastive Learning;IEEE Internet of Things Journal;2024-07-01

4. Hilogx: noise-aware log-based anomaly detection with human feedback;The VLDB Journal;2024-03-28

5. FSMFLog: Discovering Anomalous Logs Combining Full Semantic Information and Multifeature Fusion;IEEE Internet of Things Journal;2024-02-01

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