Top-k Query Optimization
Top-K Query Optimization is a query optimization technique that belongs to the class of methods aimed at minimizing computational cost for retrieving the k highest-ranked results according to a specified scoring function, distinguished by its focus on partial result set generation and early termination strategies to avoid full dataset evaluation.
134
Publications
6.9K
Citations
346
Authors
159
Institutions
Publications per year
2017–2026
25
Parents
134
Top-k Query Processing in Uncertain Databases
Mohamed A. Soliman, Ihab F. Ilyas, Kevin Chen–Chuan Chang · 2007 · 428 citations
Efficient Top-k Query Evaluation on Probabilistic Data
Christopher Ré, Nilesh Dalvi, Dan Suciu · 2007 · 374 citations
Finding Top-k Min-Cost Connected Trees in Databases
Bolin Ding, Jeffrey Xu Yu, Shan Wang et al. · 2007 · 322 citations
Chengkai Li, Kevin Chen–Chuan Chang, Ihab F. Ilyas et al. · 2005 · 275 citations
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346
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159
Chinese University of Hong Kong
Hong Kong, Hong Kong
10 h-index
15 publications
1.5K citations

Hong Kong University of Science and Technology
Hong Kong, Hong Kong
9 h-index
17 publications
917 citations
The University of Osaka
Osaka, Japan
9 h-index
30 publications
563 citations

Hunan University
Changsha, China
6 h-index
25 publications
902 citations
University of Illinois Urbana-Champaign
Urbana, United States
6 h-index
13 publications
1.7K citations

UNSW Sydney
Sydney, Australia
6 h-index
8 publications
594 citations

University of Hong Kong
Pok Fu Lam, Hong Kong
5 h-index
16 publications
890 citations

University of Waterloo
Waterloo, Canada
5 h-index
6 publications
1.3K citations
1–8 of 159
TKDE · 15 publications · 487 citations
13
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PVLDB · 8 publications · 856 citations
8
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TODS · 6 publications · 483 citations
6
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4 publications · 125 citations
4
h-index
4 publications · 150 citations
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