DBScholar

Back to papers

Improving Adaptable Similarity Query Processing by Using Approximations

Summary: Conservative approximations cut exact distance computations for adaptable quad-form similarity, enabling efficient kNN with no false drops. Experiments on synthetic data and a 112k-image color database show up to 6× speedups with multidimensional indexes. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
8680
Venue
VLDB
Year
1998
Pagerank
6.0702428e-05
Overall Rank
5,838 | 59.95%
DOI
-

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{ankerst_vldb98,
        title = {{Improving Adaptable Similarity Query Processing by Using Approximations}},
        author = {Ankerst, Mihael and Braunmüller, Bernhard and Kriegel, Hans-Peter and Seidl, Thomas},
        journal = {PVLDB},
        series = {{VLDB} '98},
        pages = {206},
        year = {1998}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 14 of 14 cited papers.

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

Previous Page 1 / 1 Next

Semantically Similar Papers