Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06)
Privacy-Preserving Data Imputation
Hong Kong, China
December 18-December 22
ISBN: 0-7695-2702-7
In this paper, we investigate privacy-preserving data imputation on distributed databases. We present a privacypreserving 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.