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)
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,009 | Constructing Efficient Decision Trees by Using Optimized Numeric Association Rules | 1996 | VLDB | 6.5356352e-05 |
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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 |
|---|---|---|---|---|
| 4,515 | Mining Optimized Association Rules for Numeric Attributes | 1996 | PODS | 6.1157444e-05 |
| 4,692 | Data Mining Using Two-Dimensional Optimized Association Rules: Scheme, Algorithms, and Visualization | 1996 | SIGMOD | 5.987105e-05 |
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| 4,009 | Constructing Efficient Decision Trees by Using Optimized Numeric Association Rules | 1996 | VLDB | 6.5356352e-05 |
| 4,692 | Data Mining Using Two-Dimensional Optimized Association Rules: Scheme, Algorithms, and Visualization | 1996 | SIGMOD | 5.987105e-05 |
| 4,515 | Mining Optimized Association Rules for Numeric Attributes | 1996 | PODS | 6.1157444e-05 |