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Efficient Searching with Linear Constraints (Extended Abstract)

Summary: External-memory data structures for reporting points satisfying a linear constraint a·x ∈ [α,β] in R^d, with focus on I/O cost. For d=2: first near-linear-space structure with optimal I/Os, plus a linear-size worst-case-efficient structure, space/query tradeoffs, and extensions to higher dimensions. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1141
Venue
PODS
Year
1998
Pagerank
0.00010361147
Overall Rank
1,561 | 89.30%
DOI
10.1145/275487.275506

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{agarwal_pods98,
        address = {New York, NY, USA},
        series = {{PODS} '98},
        title = {{Efficient Searching with Linear Constraints (Extended Abstract)}},
        url = {https://dl.acm.org/doi/10.1145/275487.275506},
        doi = {10.1145/275487.275506},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Agarwal, Pankaj K. and Arge, Lars and Erickson, Jeff and Franciosa, Paolo G. and Vitter, Jeffrey Scott},
        year = {1998}
}

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