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An Overview of the Use of Clustering for Data Privacy
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. (Skövde Artificial Intelligence Lab (SAIL))ORCID iD: 0000-0002-0368-8037
Universitat Autònoma de Barcelona, Barcelona, Spain.
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Fysik och matematik, Physics and Mathematics)ORCID iD: 0000-0002-5040-2089
2016 (English)In: Unsupervised Learning Algorithms / [ed] M. Emre Celebi, Kemal Aydin, Springer, 2016, 237-251 p.Chapter in book (Refereed)
Abstract [en]

In this chapter we review some of our results related to the use of clustering in the area of data privacy. The paper gives a brief overview of data privacy and, more specifically, on data driven methods for data privacy and discusses where clustering can be applied in this setting. We discuss the role of clustering in the definition of masking methods, and on the calculation of information loss and data utility.

Place, publisher, year, edition, pages
Springer, 2016. 237-251 p.
National Category
Computer Science
Research subject
Physics and Mathematics; Skövde Artificial Intelligence Lab (SAIL)
Identifiers
URN: urn:nbn:se:his:diva-12344DOI: 10.1007/978-3-319-24211-8_10Scopus ID: 2-s2.0-84978289110ISBN: 978-3-319-24209-5 (print)ISBN: 978-3-319-24211-8 (electronic)OAI: oai:DiVA.org:his-12344DiVA: diva2:934213
Available from: 2016-06-08 Created: 2016-06-08 Last updated: 2017-06-20Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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Output format
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