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Evaluating Top-k Selection Queries
Summary: Studies translating top-k similarity queries into a single range query executable by conventional relational DBMSs. Derives statistics-driven range selection and evaluates how cardinality/statistics quality affects retrieval efficiency.
(summarized by gpt-5.6-luna on Jul 24 2026)
Paper ID
he27a38f77f418056
Venue
VLDB
Year
1999
Pagerank
0.0001521012
Overall Rank
643 | 95.68%
DOI
10.5555/645925.673
Incoming Non-self Citations Over Time
BibTeX Citation
@article{chaudhuri_vldb99,
title = {{Evaluating Top-k Selection Queries}},
author = {Chaudhuri, Surajit and Gravano, Luis},
journal = {PVLDB},
series = {{VLDB} '99},
pages = {399--410},
doi = {10.5555/645925.673},
url = {https://doi.org/10.5555/645925.673},
year = {1999}
}
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RankSQL: Query Algebra and Optimization for Relational Top-k Queries 2005
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Outgoing Citations (Sorted by Pagerank)
Showing 12 of 12 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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