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Progressive Computation of the Min-Dist Optimal-Location Query

Summary: Introduces the min-dist optimal-location query: choose a new site in a region to minimize weighted average nearest-site distance, using L1 metrics. A finite-candidate theorem and progressive refinement provide error-bounded locations, reusable pruning, and eventual exactness. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
9669
Venue
VLDB
Year
2006
Pagerank
7.4213355e-05
Overall Rank
3,428 | 76.49%
DOI
-

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{zhang_vldb06,
        title = {{Progressive Computation of the Min-Dist Optimal-Location Query}},
        author = {Zhang, Donghui and Du, Yang and Xia, Tian and Tao, Yufei},
        journal = {PVLDB},
        series = {{VLDB} '06},
        pages = {643--654},
        year = {2006}
}

Incoming Citations (Sorted by Pagerank)

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Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
546 Influence Sets Based on Reverse Nearest Neighbor Queries 2000 SIGMOD 0.00016734556
1,612 Reverse kNN Search in Arbitrary Dimensionality 2004 VLDB 0.00010218134
1,681 Discovery of Influence Sets in Frequently Updated Databases 2001 VLDB 0.00010022485
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