Privacy preserving clustering by data transformation.

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dc.contributorSTANLEY ROBSON DE MEDEIROS OLIVEIRA, CNPTIA; OSMAR R. ZAÏANE, University of Alberta.
dc.creatorOLIVEIRA, S. R. de M.
dc.creatorZAÏANE, O. R.
dc.date2018-04-04T00:32:41Z
dc.date2018-04-04T00:32:41Z
dc.date2004-04-20
dc.date2003
dc.date2020-02-10T11:11:11Z
dc.date.accessioned2026-07-07T04:15:31Z
dc.descriptionRelated work. Basic concepts. The basics of data perturbation. The basics of imaging geometry. The family of geometric data transformation methods. Basic definitions. The translation data perturbation method. The scaling data perturbation method. The rotation data perturbation method. The hybrid data perturbation method. Experimental results. Methodology. Measuring effectiveness. Quantifying privacy. Improving privacy. Conclusions.
dc.descriptionSBBD 2003. Na publicação: Stanley R. M. Oliveira.
dc.formatp. 304-318.
dc.identifierIn: SIMPÓSIO BRASILEIRO DE BANCO DE DADOS, 18., 2003, Manaus. Anais... Manaus: Universidade Federal do Amazonas, 2003.
dc.identifierhttp://www.alice.cnptia.embrapa.br/alice/handle/doc/8874
dc.identifier.urihttp://hdl.handle.net/123456789/455783
dc.languageeng
dc.rightsopenAccess
dc.subjectPreservação de privacidade
dc.subjectClusterização
dc.subjectMineração de dados
dc.subjectData Perturbation Method
dc.subjectData mining
dc.subjectCluster analysis
dc.titlePrivacy preserving clustering by data transformation.
dc.typeArtigo em anais e proceedings

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