Bias in OLAP Queries: Detection, Explanation, and Removal (Or Think Twice About Your AVG-Query)
Summary: HypDB detects bias in OLAP queries via independence tests, explains the causes, and rewrites biased queries into unbiased forms. Real-data evaluations show accurate bias detection, actionable explanations, and automatic discovery of insights, including a landmark 1973 discrimination case. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Babak Salimi (University of Washington)
- 2. Johannes Gehrke (Microsoft)
- 3. Dan Suciu (University of Washington)
BibTeX Citation
@inproceedings{salimi_sigmod18,
title = {{Bias in OLAP Queries: Detection, Explanation, and Removal (Or Think Twice About Your AVG-Query)}},
author = {Salimi, Babak and Gehrke, Johannes and Suciu, Dan},
series = {{SIGMOD} '18},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3183713.3196914},
url = {https://dl.acm.org/doi/10.1145/3183713.3196914},
year = {2018}
}Incoming Citations (Sorted by Pagerank)
Showing 23 of 23 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,864 | Hypothetical Queries in an OLAP Environment | 2000 | VLDB | 9.4653035e-05 |
| 1,953 | Caravan: Provisioning for What-If Analysis | 2013 | CIDR | 9.297314e-05 |
| 2,848 | Towards Sustainable Insights or why polygamy is bad for you | 2017 | CIDR | 7.9234942e-05 |
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