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Evaluating Continuous Queries with Inconsistency Annotations

Summary: Introduces provenance-based inconsistency annotations for continuous queries, tracing streaming constraint violations to affected outputs without dropping or repairing data. A graph-based implementation preserves throughput under memory pressure, with annotation overhead up to 25%. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
13988
Venue
VLDB
Year
2025
Pagerank
5.093636e-05
Overall Rank
10,818 | 25.78%
DOI
10.14778/3718057.3718062

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Authors

BibTeX Citation

@article{langhi_vldb25,
        title = {{Evaluating Continuous Queries with Inconsistency Annotations}},
        author = {Langhi, Samuele and Bonifati, Angela and Tommasini, Riccardo},
        journal = {PVLDB},
        series = {{VLDB} '25},
        volume = {18},
        number = {5},
        pages = {1321--1334},
        doi = {10.14778/3718057.3718062},
        url = {https://doi.org/10.14778/3718057.3718062},
        year = {2025}
}

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