Personalized Privacy-Preserving Frequent Itemset Mining Using Randomized Response

<table>Frequent itemset added ration <svg height="14.3125" id="M227" style="vertical-align:-0.13794pt" version="1.1" viewbox="0 0 17.3375 14.3125" width="17.3375" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
<g transform="matrix(.017,-0,0,-.017,.062,14.05)"><path d="M548 455q-32 -77 -74 -77q-37 0 -103 10l-3 -2q36 -30 48.5 -62t12.5 -80q0 -103 -75 -179.5t-175 -76.5q-70 0 -113 45t-43 128q0 115 83.5 200.5t209.5 85.5q31 0 77.5 -4t67.5 -4q36 0 62 30zM350 274q0 54 -17 86q-19 35 -57 35q-50 0 -90 -37.5t-59 -91.5t-19 -109
q0 -61 24.5 -96.5t65.5 -35.5q51 0 87.5 46.5t50.5 100.5t14 102z" id="x1D70E"></path></g>
<g transform="matrix(.012,-0,0,-.012,9.663,5.887)"><path d="M535 230h-212v-233h-58v233h-213v50h213v210h58v-210h212v-50z" id="x2B"></path></g>
</svg> versus minimum support on different size of datasets.</table>

The Scientific World Journal

fig11

Figure 11

Figure 11: Personalized Privacy-Preserving Frequent Itemset Mining Using Randomized Response 