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Quantitative Association Rules Mining Methods with Privacy-preserving
Sixth International Conference on Parallel and Distributed Computing Applications and Technologies (PDCAT'05), 2005Considering the different size of quantitative attribute values and categorical attribute values in databases, we present two quantitative association rules mining methods with privacy-preserving respectively, one bases on Boolean association rules, which is suitable for the smaller size of quantitative attribute values and categorical attribute values
Zi-Yang Chen, Guo-hua Liu
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A Statistical Theory for Quantitative Association Rules
Journal of Intelligent Information Systems, 1999Association rules are a key data-mining tool and as such have been well researched. So far, this research has focused predominantly on databases containing categorical data only. However, many real-world databases contain quantitative attributes and current solutions for this case are so far inadequate.
Yonatan Aumann, Yehuda Lindell
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