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The main contribution of this paper lies in the algorithm to accurately reconstruct the community joint density given the perturbed multidimensional stream data information. Any statistical question about the community can be answered using the reconstructed joint density. There have been many efforts on the community distribution reconstruction. In this paper, the authors are considering the information privacy which now-a-days has become one of the most important issues. They touch upon several techniques of masking the data, namely random distortion, including the uniform and Gaussian noise, applied to the data in order to protect it.
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