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Robust and Transferable Log-based Anomaly Detection

Summary: RT-Log introduces adaptive relation modeling over multi-field log information to capture selective feature interactions for robust anomaly detection. It also proposes environment generalization to learn environment-invariant representations, enabling transferability across dynamic runtimes; results on real data show consistent improvements over SOTA. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6629
Venue
SIGMOD
Year
2023
Pagerank
7.4605908e-05
Overall Rank
3,376 | 76.84%
DOI
10.1145/3588918

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{jia_sigmod23,
        title = {{Robust and Transferable Log-based Anomaly Detection}},
        author = {Jia, Peng and Cai, Shaofeng and Ooi, Beng Chin and Wang, Pinghui and Xiong, Yiyuan},
        series = {{SIGMOD} '23},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3588918},
        url = {https://dl.acm.org/doi/10.1145/3588918},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

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Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
1,235 Towards Linear Algebra over Normalized Data 2017 VLDB 0.00011548457
2,179 Enabling and Optimizing Non-linear Feature Interactions in Factorized Linear Algebra 2019 SIGMOD 9.0146333e-05
4,390 ARM-Net: Adaptive Relation Modeling Network for Structured Data 2021 SIGMOD 6.7290926e-05
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