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GORDER: An Efficient Method for KNN Join Processing

Summary: GORDER: a G-ordering KNN-join via a block-nested-loop (BNLJ) for high-dimensional data. It uses G-order sorting, scheduled BNLJ, and distance filtering/reduction to reduce I/O and CPU, achieving wide-margin gains over existing KNN-join methods. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
9184
Venue
VLDB
Year
2004
Pagerank
5.3981191e-05
Overall Rank
5,636 | 60.80%
DOI
-

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Incoming Citations (Sorted by Pagerank)

Showing 5 of 5 citing papers.

Rank Citing Paper Year Venue Pagerank
1,931 Efficient Processing of k Nearest Neighbor Joins using MapReduce 2012 VLDB 0.00010040427
4,808 On the Complexity of Inner Product Similarity Join 2016 PODS 5.908896e-05
6,770 An Incremental Hausdorff Distance Calculation Algorithm 2011 VLDB 4.9317829e-05
8,629 Spatial Queries with Two kNN Predicates 2012 VLDB 4.4809879e-05
9,347 Rank Join Queries in NoSQL Databases 2014 VLDB 4.3526718e-05
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