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Optimal Grid-Clustering: Towards Breaking the Curse of Dimensionality in High-Dimensional Clustering

Summary: OptiGrid introduces optimal grid-partitioning for high-dimensional clustering, selecting dimension-wise hyperplane splits via projections to beat the curse of dimensionality. It outperforms condensation-based methods like BIRCH, offering a solid mathematical basis, improved effectiveness in high dimensions, and scalable efficiency on large real datasets (CAD, molecular biology). (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
hc9247356c8882ba6
Venue
VLDB
Year
1999
Pagerank
7.0336098e-05
Overall Rank
3,750 | 74.87%
DOI
-

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{hinneburg_vldb99,
        title = {{Optimal Grid-Clustering: Towards Breaking the Curse of Dimensionality in High-Dimensional Clustering}},
        author = {Hinneburg, Alexander and Keim, Daniel A.},
        journal = {PVLDB},
        series = {{VLDB} '99},
        pages = {506--517},
        year = {1999}
}

Incoming Citations (Sorted by Pagerank)

Showing 7 of 7 citing papers.

Rank Citing Paper Year Venue Pagerank
2,006 SQLEM: Fast Clustering in SQL using the EM Algorithm 2000 SIGMOD 9.1840961e-05
2,795 DADA: A Data Cube for Dominant Relationship Analysis 2006 SIGMOD 7.9865595e-05
3,627 A Monte Carlo Algorithm for Fast Projective Clustering 2002 SIGMOD 7.1290231e-05
5,647 Combi-Operator – Database Support for Data Mining Applications 2003 VLDB 6.0352838e-05
7,185 C2P: Clustering based on Closest Pairs 2001 VLDB 5.5746325e-05
8,406 CURLER: Finding and Visualizing Nonlinear Correlation Clusters 2005 SIGMOD 5.3223662e-05
13,101 k-Means Projective Clustering 2004 PODS 4.9605343e-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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