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Rethinking Choices for Multi-dimensional Point Indexing: Making the Case for the Often Ignored Quadtree

Summary: Challenges R*-tree dominance for low-to-medium dimensional point indexing, showing Quadtree’s regular, disjoint decomposition dramatically reduces MBR overlap and yields structural/search advantages. Analytical models and extensive experiments show quadtrees (despite being unbalanced) improve buffer-pool utilization and outperform R*-trees and the Pyramid technique on point workloads, motivating their reconsideration. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
86
Venue
CIDR
Year
2007
Pagerank
5.279561e-05
Overall Rank
9,365 | 35.75%
DOI
-

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{kim_cidr07,
        address = {Amsterdam, Netherlands},
        series = {{CIDR} '07},
        title = {{Rethinking Choices for Multi-dimensional Point Indexing: Making the Case for the Often Ignored Quadtree}},
        booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
        author = {Kim, You Jung and Patel, Jignesh M.},
        year = {2007}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
7,632 K-Anonymization as Spatial Indexing: Toward Scalable and Incremental Anonymization 2007 VLDB 5.5777517e-05
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