Importance partitioning in micro-aggregation

Kokolakis, G; Fouskakis, D

dc.contributor.author	Kokolakis, G	en
dc.contributor.author	Fouskakis, D	en
dc.date.accessioned	2014-03-01T01:30:52Z
dc.date.available	2014-03-01T01:30:52Z
dc.date.issued	2009	en
dc.identifier.issn	0167-9473	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/19665
dc.subject	Heuristic Algorithm	en
dc.subject	Heuristic Method	en
dc.subject	Information Loss	en
dc.subject	Polynomial Algorithm	en
dc.subject.classification	Computer Science, Interdisciplinary Applications	en
dc.subject.classification	Statistics & Probability	en
dc.subject.other	Heuristic algorithms	en
dc.subject.other	Continuous datum	en
dc.subject.other	Data distortions	en
dc.subject.other	Information loss	en
dc.subject.other	Polynomial algorithms	en
dc.subject.other	Small groups	en
dc.subject.other	Heuristic methods	en
dc.title	Importance partitioning in micro-aggregation	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.csda.2008.09.028	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.csda.2008.09.028	en
heal.language	English	en
heal.publicationDate	2009	en
heal.abstract	One of the techniques of data holders for the protection of confidentiality of continuous data is that of micro-aggregation. Rather than releasing raw data (individual records), micro-aggregation releases the averages of small groups and thus reduces the risk of identity disclosure. At the same time the method implies loss of information and often distorts the data. Thus, the choice of groups is very crucial to minimize the information loss and the data distortion. No exact polynomial algorithms exist up to date for optimal microaggregation, and so the usage of heuristic methods is necessary. A heuristic algorithm, based on the notion of importance partitioning, is proposed and it is shown that compared with other micro-aggregation heuristics achieves improved performance. (C) 2008 Elsevier B.V. All rights reserved.	en
heal.publisher	ELSEVIER SCIENCE BV	en
heal.journalName	Computational Statistics and Data Analysis	en
dc.identifier.doi	10.1016/j.csda.2008.09.028	en
dc.identifier.isi	ISI:000264907600001	en
dc.identifier.volume	53	en
dc.identifier.issue	7	en
dc.identifier.spage	2439	en
dc.identifier.epage	2445	en