How to Quickly Find a Witness
Summary: Introduce the "witness" concept to decouple traversal from pruning in constrained itemset mining, enabling existing algorithms to handle arbitrary, non-(anti)monotone/convertible constraints. Provide efficient witness-finding for stable functions and variance constraints (var(S) ≤ c, ≥ c) with heuristics to accelerate mining. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Daniel Kifer (Cornell University)
- 2. Johannes Gehrke (Cornell University)
- 3. Cristian Bucila (Cornell University)
- 4. Walker White (University of Dallas)
BibTeX Citation
@inproceedings{kifer_pods03,
address = {New York, NY, USA},
series = {{PODS} '03},
title = {{How to Quickly Find a Witness}},
url = {https://dl.acm.org/doi/10.1145/773153.773180},
doi = {10.1145/773153.773180},
booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
publisher = {Association for Computing Machinery},
author = {Kifer, Daniel and Gehrke, Johannes and Bucila, Cristian and White, Walker},
year = {2003}
}
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Outgoing 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 |
|---|---|---|---|---|
| 13 | Mining Association Rules between Sets of Items in Large Databases | 1993 | SIGMOD | 0.0006567919 |
| 1,535 | Exploratory Mining and Pruning Optimizations of Constrained Association Rules | 1998 | SIGMOD | 0.00010463058 |
| 4,969 | Optimization of Constrained Frequent Set Queries with 2-variable Constraints | 1999 | SIGMOD | 6.4201643e-05 |
| 6,578 | Data mining, Hypergraph Transversals, and Machine Learning | 1997 | PODS | 5.8364579e-05 |
| 6,719 | Exploratory Mining via Constrained Frequent Set Queries | 1999 | SIGMOD | 5.7944032e-05 |
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