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Approximate NN Queries on Streams with Guaranteed Error/performance Bounds

Summary: Introduces e-approximate kNN (ekNN) on data streams with an absolute error bound on the k-th distance. Proposes DISC, adaptive space-filling-curve indexing that trades memory for accuracy in streaming workloads, with fast updates and strong empirical validation. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
9379
Venue
VLDB
Year
2004
Pagerank
7.9957585e-05
Overall Rank
2,886 | 80.21%
DOI
10.1016/B978-012088469-8.50071-1

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{koudas_vldb04,
        title = {{Approximate NN Queries on Streams with Guaranteed Error/performance Bounds}},
        author = {Koudas, Nick and Ooi, Beng Chin and Tan, Kian-Lee and Zhang, Rui},
        journal = {PVLDB},
        series = {{VLDB} '04},
        pages = {804--815},
        doi = {10.1016/B978-012088469-8.50071-1},
        url = {https://doi.org/10.1016/B978-012088469-8.50071-1},
        year = {2004}
}

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