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Privacy-Preserving Data Imputation
Hong Kong, China December 18-December 22
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDMW.2006.134Sixth IEEE International Conference o ...
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Geetha Jagannathan, Rebecca N. Wright, "Privacy-Preserving Data Imputation," Data Mining Workshops, International Conference on, pp. 535-540, Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06), 2006.
 
 
BibTex
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@article{ 10.1109/ICDMW.2006.134,
author = {Geetha Jagannathan and Rebecca N. Wright},
title = {Privacy-Preserving Data Imputation},
journal ={Data Mining Workshops, International Conference on},
volume = {0},
year = {2006},
isbn = {0-7695-2702-7},
pages = {535-540},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICDMW.2006.134},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Data Mining Workshops, International Conference on
TI - Privacy-Preserving Data Imputation
SN - 0-7695-2702-7
SP535
EP540
A1 - Geetha Jagannathan,
A1 - Rebecca N. Wright,
PY - 2006
KW - null
VL - 0
JA - Data Mining Workshops, International Conference on
ER -
 
Geetha Jagannathan, Stevens Institute of Technology, Hoboken, NJ
Rebecca N. Wright, Stevens Institute of Technology, Hoboken, NJ
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.
Citation:
Geetha Jagannathan, Rebecca N. Wright, "Privacy-Preserving Data Imputation," icdmw, pp.535-540, Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06), 2006
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