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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)

Paper ID
2987
Venue
SIGMOD
Year
1996
Pagerank
-
Overall Rank
14,223 | 2.42%
DOI
10.1145/233269.280359

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Authors

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}
}

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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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