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Uniform Generation in Spatial Constraint Databases and Applications

Summary: Extends Dyer–Frieze–Kannan sampling to linear-constraint databases, yielding almost-uniform generators for DNF unions and for projections, with conditions for intersections/differences to enable relative-volume estimates. Combines sample convex-hull reconstruction to approximate relations and reconstruct sets for positive-existential queries. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1214
Venue
PODS
Year
2000
Pagerank
5.093636e-05
Overall Rank
12,879 | 11.64%
DOI
10.1145/335168.335228

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BibTeX Citation

@inproceedings{gross_pods00,
        address = {New York, NY, USA},
        series = {{PODS} '00},
        title = {{Uniform Generation in Spatial Constraint Databases and Applications}},
        url = {https://dl.acm.org/doi/10.1145/335168.335228},
        doi = {10.1145/335168.335228},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Gross, David and de Rougemont, Michel},
        year = {2000}
}

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