SONAR: System for Optimized Numeric Association Rules
Summary: SONAR mines optimized association rules from numeric and Boolean data by choosing support and confidence ranges to maximize rule quality under a threshold. It yields 2D rules on (Age, Balance) with rectangles or admissible (connected, x-monotone) regions, defining optimized support and confidence per region class. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
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Authors
- 1. Takeshi Fukuda (IBM)
- 2. Yasuhiko Morimoto (IBM)
- 3. Shinichi Morishita (IBM)
- 4. Takeshi Tokuyama (IBM)
BibTeX Citation
@inproceedings{fukuda_sigmod96,
title = {{SONAR: System for Optimized Numeric Association Rules}},
author = {Fukuda, Takeshi and Morimoto, Yasuhiko and Morishita, Shinichi and Tokuyama, Takeshi},
series = {{SIGMOD} '96},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/233269.280359},
url = {https://dl.acm.org/doi/10.1145/233269.280359},
year = {1996}
}
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,509 | Constructing Efficient Decision Trees by Using Optimized Numeric Association Rules | 1996 | VLDB | 6.6548619e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,565 | Data Mining Using Two-Dimensional Optimized Association Rules: Scheme, Algorithms, and Visualization | 1996 | SIGMOD | 6.6278063e-05 |
| 4,766 | Mining Optimized Association Rules for Numeric Attributes | 1996 | PODS | 6.5181854e-05 |
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