A New Algorithm for Finding Minimal Sample Uniques for Use in Statistical Disclosure Assessment

I
ICDM
2005
Fifth IEEE International Conference on Data Mining (ICDM'05)
Abstract - A New Algorithm for Finding Minimal Sample Uniques for Use in Statistical Disclosure Assessment

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	Similar Articles Articles by A. M. Manning Articles by D. J. Haglin

Fifth IEEE International Conference on Data Mining (ICDM'05)

Houston, Texas

November 27-November 30

ISBN: 0-7695-2278-5

	ASCII Text	x
	A. M. Manning, D. J. Haglin, "A New Algorithm for Finding Minimal Sample Uniques for Use in Statistical Disclosure Assessment," Data Mining, IEEE International Conference on, pp. 290-297, Fifth IEEE International Conference on Data Mining (ICDM'05), 2005.

	BibTex	x
	@article{ 10.1109/ICDM.2005.10, author = {A. M. Manning and D. J. Haglin}, title = {A New Algorithm for Finding Minimal Sample Uniques for Use in Statistical Disclosure Assessment}, journal ={Data Mining, IEEE International Conference on}, volume = {0}, year = {2005}, issn = {1550-4786}, pages = {290-297}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICDM.2005.10}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Data Mining, IEEE International Conference on TI - A New Algorithm for Finding Minimal Sample Uniques for Use in Statistical Disclosure Assessment SN - 1550-4786 SP290 EP297 A1 - A. M. Manning, A1 - D. J. Haglin, PY - 2005 KW - null VL - 0 JA - Data Mining, IEEE International Conference on ER -

A. M. Manning, University of Manchester

D. J. Haglin, Minnesota State University

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDM.2005.10

We present SUDA2, a recursive algorithm for finding Minimal Sample Uniques (MSUs). SUDA2 uses a novel method for representing the search space forMSUs and new observations about the properties ofMSUs to prune and traverse this space. Experimental comparisons with previous work demonstrate that SUDA2 is not only several orders of magnitude faster but is also capable of identifying the boundaries of the search space, enabling datasets of larger numbers of columns than before to be addressed.

Citation:

A. M. Manning, D. J. Haglin, "A New Algorithm for Finding Minimal Sample Uniques for Use in Statistical Disclosure Assessment," icdm, pp.290-297, Fifth IEEE International Conference on Data Mining (ICDM'05), 2005

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