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Benchmarking Approximate Consistent Query Answering

Summary: Benchmarks randomized schemes to approximate the fraction of repairs where an answer holds in CQA for conjunctive queries with primary-key violations. Extensive experiments relate method performance to data/query traits and show approximate CQA is practical. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1836
Venue
PODS
Year
2021
Pagerank
5.8066263e-05
Overall Rank
6,674 | 54.22%
DOI
10.1145/3452021.3458309

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{calautti_pods21,
        address = {New York, NY, USA},
        series = {{PODS} '21},
        title = {{Benchmarking Approximate Consistent Query Answering}},
        url = {https://dl.acm.org/doi/10.1145/3452021.3458309},
        doi = {10.1145/3452021.3458309},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Calautti, Marco and Console, Marco and Pieris, Andreas},
        year = {2021}
}

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