Mining Flipping Correlations from Large Datasets with Taxonomies
Summary: Introduces flipping correlations by contrasting correlations across abstraction levels, yielding sign changes under generalization. Flipper outperforms naive mining by orders of magnitude and finds surprising correlations at low-to-medium support. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Marina Barsky (University of Victoria)
- 2. Sangkyum Kim (University of Illinois Urbana-Champaign)
- 3. Tim Weninger (University of Illinois Urbana-Champaign)
- 4. Jiawei Han (University of Illinois Urbana-Champaign)
BibTeX Citation
@article{barsky_vldb12,
title = {{Mining Flipping Correlations from Large Datasets with Taxonomies}},
author = {Barsky, Marina and Kim, Sangkyum and Weninger, Tim and Han, Jiawei},
journal = {PVLDB},
series = {{VLDB} '12},
volume = {5},
number = {4},
pages = {370--381},
doi = {10.14778/2095686.2095695},
url = {https://doi.org/10.14778/2095686.2095695},
year = {2012}
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Showing 5 of 5 cited papers.
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 | 0.00064420972 |
| 164 | Mining Frequent Patterns without Candidate Generation | 2000 | SIGMOD | 0.00027412227 |
| 467 | Discovery of Multiple-Level Association Rules from Large Databases | 1995 | VLDB | 0.00017766906 |
| 475 | Mining Generalized Association Rules | 1995 | VLDB | 0.00017672519 |
| 731 | Beyond Market Baskets: Generalizing Association Rules to Correlations | 1997 | SIGMOD | 0.00014394521 |
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