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Skyline Queries with Noisy Comparisons

Summary: Introduces a noisy-comparison model for skyline queries (pairwise comparisons may err; confidence via repetition) and gives the first output-sensitive algorithms that minimize comparisons and rounds to compute/verify skylines w.h.p. Shows optimal skyline prediction from partial noisy comparisons is computationally intractable. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
h19b5812fa8c8079a
Venue
PODS
Year
2015
Pagerank
5.0580396e-05
Overall Rank
10,219 | 31.30%
DOI
10.1145/2745754.2745775

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{groz_pods15,
        address = {New York, NY, USA},
        series = {{PODS} '15},
        title = {{Skyline Queries with Noisy Comparisons}},
        url = {https://dl.acm.org/doi/10.1145/2745754.2745775},
        doi = {10.1145/2745754.2745775},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Groz, Benoit and Milo, Tova},
        year = {2015}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
7,500 Crowdsourced Data Management: Overview and Challenges 2017 SIGMOD 5.5083793e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 4 of 4 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
266 Human-powered Sorts and Joins 2012 VLDB 0.00022739124
313 Shooting Stars in the Sky: An Online Algorithm for Skyline Queries 2002 VLDB 0.00021311041
749 So Who Won? Dynamic Max Discovery with the Crowd 2012 SIGMOD 0.00014265279
1,124 Probabilistic Skylines on Uncertain Data 2007 VLDB 0.00011927351
Previous Page 1 / 1 Next

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