Ranking Distributed Probabilistic Data
Summary: Top-k ranking for distributed probabilistic data, using the expected rank across possible worlds as the criterion. Designs both communication- and computation-efficient algorithms to obtain the global top-k with minimum data transfer. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Feifei Li (Florida State University)
- 2. Ke Yi (Hong Kong University of Science and Technology)
- 3. Jeffrey Jestes (Florida State University)
BibTeX Citation
@inproceedings{li_sigmod09,
title = {{Ranking Distributed Probabilistic Data}},
author = {Li, Feifei and Yi, Ke and Jestes, Jeffrey},
series = {{SIGMOD} '09},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/1559845.1559885},
url = {https://dl.acm.org/doi/10.1145/1559845.1559885},
year = {2009}
}
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,044 | Threshold Query Optimization for Uncertain Data | 2010 | SIGMOD | 5.3253644e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 17 of 17 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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