A Max-Min Approach for Hiding Frequent Itemsets
George V. Moustakides, Vassilios S. Verykios · 2006
In this paper we are proposing a new algorithmic approach for sanitizing raw data from sensitive knowledge in the context of mining of association rules. The new approach (a) relies on the maxmin criterion which is a method in decision theory for maximizing the minimum gain, and (b) builds upon the border theory of frequent itemsets