A New Method for Preserving Privacy in Quantitative Association Rules Using Genetic Algorithm

Data mining is the process of extracting hidden patterns from data. With the explosion of data, data mining is essential to extract useful information. Association rule mining is a method for finding correlation among large set of data items. A rule is characterized as sensitive if its disclosure risk is above a certain confidence value. Sensitive rules should not be disclosed to the public, as they can be used to infer sensitive data and provide an advantage for the business competitors. Techniques for hiding association rules are almost limited to binary items. But, real world data mostly consists of quantitative values.

Provided by: International Journal of Computer Applications Topic: Big Data Date Added: Dec 2012 Format: PDF

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