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ConfSeer: Leveraging Customer Support Knowledge Bases for Automated Misconfiguration Detection

Summary: ConfSeer mines natural-language customer-support KBs to detect configuration deviations and recommend fixes, addressing high-dimensional parameter matching via NLP, IR, and interactive learning. Deployed on tens of thousands of servers, it achieves 80–97.5% accuracy with low overhead. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
11248
Venue
VLDB
Year
2015
Pagerank
5.093636e-05
Overall Rank
12,128 | 16.80%
DOI
10.14778/2824032.2824036

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BibTeX Citation

@article{potharaju_vldb15,
        title = {{ConfSeer: Leveraging Customer Support Knowledge Bases for Automated Misconfiguration Detection}},
        author = {Potharaju, Rahul and Chan, Joseph and Hu, Luhui and Nita-Rotaru, Cristina and Wang, Mingshi and Zhang, Liyuan and Jain, Navendu},
        journal = {PVLDB},
        series = {{VLDB} '15},
        volume = {8},
        number = {12},
        pages = {1828--1839},
        doi = {10.14778/2824032.2824036},
        url = {https://doi.org/10.14778/2824032.2824036},
        year = {2015}
}

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