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Querying Uncertain Data with Aggregate Constraints

Summary: Uncertain data with aggregate constraints on record sets makes finding qualified possible worlds by per-tuple sampling inefficient. The paper proposes constraint-aware sampling and MCMC sampling to produce high-quality query results for uncertain data under aggregate constraints with reasonable cost. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4496
Venue
SIGMOD
Year
2011
Pagerank
6.0615445e-05
Overall Rank
5,866 | 59.76%
DOI
10.1145/1989323.1989409

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{yang_sigmod11,
        title = {{Querying Uncertain Data with Aggregate Constraints}},
        author = {Yang, Mohan and Wang, Haixun and Chen, Haiquan and Ku, Wei-Shinn},
        series = {{SIGMOD} '11},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1989323.1989409},
        url = {https://dl.acm.org/doi/10.1145/1989323.1989409},
        year = {2011}
}

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