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Filter Trees for Managing Spatial Data Over a Range of Size Granularities

Summary: Introduces Filter Trees, a hierarchical spatial file organization that stratifies entities by size and orders each level along a Hilbert curve. Bulk-I/O-aware range-query and spatial-join algorithms substantially outperform competing methods, especially for full joins. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
8519
Venue
VLDB
Year
1996
Pagerank
6.3194496e-05
Overall Rank
5,202 | 64.32%
DOI
-

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{sevcik_vldb96,
        title = {{Filter Trees for Managing Spatial Data Over a Range of Size Granularities}},
        author = {Sevcik, Kenneth C. and Koudas, Nikos},
        journal = {PVLDB},
        series = {{VLDB} '96},
        year = {1996}
}

Incoming Citations (Sorted by Pagerank)

Showing 5 of 5 citing papers.

Rank Citing Paper Year Venue Pagerank
2,648 On Effective Multi-Dimensional Indexing for Strings 2000 SIGMOD 8.2957097e-05
3,066 Size Separation Spatial Join 1997 SIGMOD 7.7941163e-05
5,932 Spatial Join Selectivity Using Power Laws 2000 SIGMOD 6.0369275e-05
6,491 Two-dimensional Substring Indexing 2001 PODS 5.8641664e-05
7,070 Indexing Methods for Moving Object Databases: Games and Other Applications 2013 SIGMOD 5.7116663e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

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

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