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Contorting High Dimensional Data for Efficient Main Memory KNN Processing

Summary: Delta-tree is a multi-level main-memory index for high-dimensional KNN, where leaves store full dimensions and upper levels use PCA-projected spaces to prune search and speed distance computations. Delta+-tree adds clustering with regional partitioning; experiments show superior performance across diverse datasets. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
3518
Venue
SIGMOD
Year
2003
Pagerank
5.3766157e-05
Overall Rank
8,765 | 39.87%
DOI
10.1145/872757.872815

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{cui_sigmod03,
        title = {{Contorting High Dimensional Data for Efficient Main Memory KNN Processing}},
        author = {Cui, Bin and Ooi, Beng Chin and Su, Jianwen and Tan, Kian-Lee},
        series = {{SIGMOD} '03},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/872757.872815},
        url = {https://dl.acm.org/doi/10.1145/872757.872815},
        year = {2003}
}

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Rank Citing Paper Year Venue Pagerank
12,714 Indexing for Function Approximation 2006 VLDB 5.093636e-05
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