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GORDER: An Efficient Method for KNN Join Processing

Summary: GORDER accelerates high-dimensional KNN joins by G-ordering data and scheduling block-nested-loop comparisons. Distance-computation filtering/reduction cuts CPU and I/O costs, substantially outperforming prior methods on clustered and real datasets. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
9375
Venue
VLDB
Year
2004
Pagerank
6.2291247e-05
Overall Rank
5,405 | 62.92%
DOI
10.1016/B978-012088469-8.50067-X

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{xia_vldb04,
        title = {{GORDER: An Efficient Method for KNN Join Processing}},
        author = {Xia, Chenyi and Lu, Hongjun and Ooi, Beng Chin and Hu, Jing},
        journal = {PVLDB},
        series = {{VLDB} '04},
        pages = {756},
        doi = {10.1016/B978-012088469-8.50067-X},
        url = {https://doi.org/10.1016/B978-012088469-8.50067-X},
        year = {2004}
}

Incoming Citations (Sorted by Pagerank)

Showing 5 of 5 citing papers.

Rank Citing Paper Year Venue Pagerank
2,137 Efficient Processing of k Nearest Neighbor Joins using MapReduce 2012 VLDB 9.110238e-05
3,806 On the Complexity of Inner Product Similarity Join 2016 PODS 7.108802e-05
6,749 An Incremental Hausdorff Distance Calculation Algorithm 2011 VLDB 5.7844585e-05
8,659 Spatial Queries with Two kNN Predicates 2012 VLDB 5.3904242e-05
9,497 Rank Join Queries in NoSQL Databases 2014 VLDB 5.2608378e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 11 of 11 cited papers.

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

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