Ranking with Uncertain Scoring Functions: Semantics and Sensitivity Measures
Summary: Investigates ranking with uncertain/incomplete scoring functions (weight ranges, partial preferences) rather than fixed weights. Delivers formal semantics and sensitivity measures, with efficient techniques for interactive top-K under uncertainty. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Mohamed A. Soliman (Greenplum)
- 2. Ihab F. Ilyas (University of Waterloo)
- 3. Davide Martinenghi (Politecnico di Milano)
- 4. Marco Tagliasacchi (Politecnico di Milano)
BibTeX Citation
@inproceedings{soliman_sigmod11,
title = {{Ranking with Uncertain Scoring Functions: Semantics and Sensitivity Measures}},
author = {Soliman, Mohamed A. and Ilyas, Ihab F. and Martinenghi, Davide and Tagliasacchi, Marco},
series = {{SIGMOD} '11},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/1989323.1989408},
url = {https://dl.acm.org/doi/10.1145/1989323.1989408},
year = {2011}
}
Incoming Citations (Sorted by Pagerank)
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 333 | The Onion Technique: Indexing for Linear Optimization Queries | 2000 | SIGMOD | 0.0002089582 |
| 499 | Supporting Incremental Join Queries on Ranked Inputs | 2001 | VLDB | 0.00017431827 |
| 509 | Supporting Top-k Join Queries in Relational Databases | 2003 | VLDB | 0.00017220967 |
| 3,483 | Consensus Answers for Queries over Probabilistic Databases | 2009 | PODS | 7.372823e-05 |
| 3,823 | Ranking Continuous Probabilistic Datasets | 2010 | VLDB | 7.092508e-05 |
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