URank: Formulation and Efficient Evaluation of Top-k Queries in Uncertain Databases
Summary: URank formulates top-k queries over uncertain databases using possible-worlds semantics. It fuses score-based and probability-based ranking via a new processing framework atop existing query engines, enabling efficient search for meaningful top-k results. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Mohamed A. Soliman (University of Waterloo)
- 2. Ihab F. Ilyas (University of Waterloo)
- 3. Kevin Chen-Chuan Chang (University of Illinois Urbana-Champaign)
BibTeX Citation
@inproceedings{soliman_sigmod07,
title = {{URank: Formulation and Efficient Evaluation of Top-k Queries in Uncertain Databases}},
author = {Soliman, Mohamed A. and Ilyas, Ihab F. and Chang, Kevin Chen-Chuan},
series = {{SIGMOD} '07},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/1247480.1247613},
url = {https://dl.acm.org/doi/10.1145/1247480.1247613},
year = {2007}
}Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,248 | Threshold Query Optimization for Uncertain Data | 2010 | SIGMOD | 5.1862157e-05 |
| 9,541 | Computing All Skyline Probabilities for Uncertain Data | 2009 | PODS | 5.151324e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 85 | ULDBs: Databases with Uncertainty and Lineage | 2006 | VLDB | 0.00035848027 |
| 941 | RankSQL: Query Algebra and Optimization for Relational Top-k Queries | 2005 | SIGMOD | 0.00012938573 |
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