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Unformatted text preview: If 4 < k then we need data generalization ! V_E = [d_E, d_Z] = [1, 0] not [0, 1] Note: move one step at a time. 4 8 Step 3.2: the generalize() function Each single attribute must satisfy kanonymity E > MGT[E] Value v = a > freq(a, MGT[E]) = ? If 4 < k then what does this mean? V_E = [d_E, d_Z] = [1, 0] MGT < generalize(MGT, V_E, [0,0]) 4 9 Step 3.2: the generalize() function Each single attribute must satisfy kanonymity MGT < generalize(MGT, v, h) Generalize() transform MGT based on a generalization strategy specified by v, h. 10 Step 3.3: update the history vector Each single attribute must satisfy kanonymity Can you give me an example to illustrate how step 3.3 works? History [d_E, d_Z] = [0, 0] V_E = [1, 0] New History [0, 0] + [1, 0] = [1, 0]...
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This note was uploaded on 12/07/2011 for the course COMP 7370 taught by Professor Qin,x during the Summer '08 term at Auburn University.
 Summer '08
 Qin,X

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