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STING: A Statistical Information Grid Approach to Spatial Data Mining

Summary: STING uses a hierarchical statistical-information grid to summarize spatial cells, enabling clustering and region queries without scanning individual objects. Its coarse-to-fine summaries deliver order-of-magnitude speedups on very large spatial datasets. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
8610
Venue
VLDB
Year
1997
Pagerank
0.00011321748
Overall Rank
1,285 | 91.19%
DOI
-

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{wang_vldb97,
        title = {{STING: A Statistical Information Grid Approach to Spatial Data Mining}},
        author = {Wang, Wei and Yang, Jiong and Muntz, Richard},
        journal = {PVLDB},
        series = {{VLDB} '97},
        pages = {186--195},
        year = {1997}
}

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
31 BIRCH: An Efficient Data Clustering Method for Very Large Databases 1996 SIGMOD 0.00050347119
88 Efficient and Effective Clustering Methods for Spatial Data Mining 1994 VLDB 0.00035240327
650 The Sequoia 2000 Storage Benchmark 1993 SIGMOD 0.00015319951
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