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| Citation |
Proceedings of the ICDM International Workshop on Privacy Aspects of Data Mining, 2006.
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| Authors |
Geetha Jagannathan
Rebecca N. Wright |
In this paper, we investigate privacy-preserving data imputation on distributed databases. We present a privacy-preserving protocol for filling in missing values using a lazy decision tree imputation algorithm for data that is horizontally partitioned between two parties. The participants of the protocol learn only the imputed values; the computed decision tree is not learned by either party.