1 Ocak 2010 Dergi makalesi Açık Erişim

Abul, Osman; Bonchi, Francesco; Nanni, Mirco

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  <identifier identifierType="URL">https://aperta.ulakbim.gov.tr/record/27775</identifier>
  <creators>
    <creator>
      <creatorName>Abul, Osman</creatorName>
      <givenName>Osman</givenName>
      <familyName>Abul</familyName>
      <affiliation>TOBB Univ Econ &amp; Technol, Dept Comp Engn, Ankara, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Bonchi, Francesco</creatorName>
      <givenName>Francesco</givenName>
      <familyName>Bonchi</familyName>
      <affiliation>Yahoo Res, Barcelona 08018, Spain</affiliation>
    </creator>
    <creator>
      <creatorName>Nanni, Mirco</creatorName>
      <givenName>Mirco</givenName>
      <familyName>Nanni</familyName>
      <affiliation>CNR, ISTI, Area Ric Pisa, Pisa KDD Lab, I-56124 Pisa, Italy</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Anonymization Of Moving Objects Databases By Clustering And Perturbation</title>
  </titles>
  <publisher>Aperta</publisher>
  <publicationYear>2010</publicationYear>
  <dates>
    <date dateType="Issued">2010-01-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Journal article</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/27775</alternateIdentifier>
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  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1016/j.is.2010.05.003</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
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  <descriptions>
    <description descriptionType="Abstract">Preserving individual privacy when publishing data is a problem that is receiving increasing attention. Thanks to its simplicity the concept of k-anonymity, introduced by Samarati and Sweeney [1], established itself as one fundamental principle for privacy preserving data publishing. According to the k-anonymity principle, each release of data must be such that each individual is indistinguishable from at least k-1 other individuals.</description>
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