Optimizing Multi-Feature Queries for Image Databases
Summary: Introduces Quick-Combine, a multi-feature top-k retrieval algorithm for image databases with flexible score aggregation and incremental top-k output. Improves termination over Fagin's algorithm with a score-distribution-aware heuristic, delivering large speedups (up to 30x) on skewed data and scalable benchmarks. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Ulrich Güntzer (University of Tübingen)
- 2. Wolf-Tilo Balke (University of Augsburg)
- 3. Werner Kießling (University of Augsburg)
BibTeX Citation
@article{guntzer_vldb00,
title = {{Optimizing Multi-Feature Queries for Image Databases}},
author = {Güntzer, Ulrich and Balke, Wolf-Tilo and Kießling, Werner},
journal = {PVLDB},
series = {{VLDB} '00},
volume = {26},
pages = {419--430},
year = {2000}
}
Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 170 | Combining Fuzzy Information from Multiple Systems | 1996 | PODS | 0.00027376361 |
| 402 | Fuzzy Queries in Multimedia Database Systems | 1998 | PODS | 0.00019072958 |
| 675 | Optimizing Queries over Multimedia Repositories | 1996 | SIGMOD | 0.00015080025 |
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