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Privacy preserving publication of transactional data /

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dc.contributor.authorBewong. Michael,
dc.contributor.schoolUniversity of South Australia. School of Information Technology and Mathematical Sciences.
dc.contributor.schoolSchool of Information Technology and Mathematical Sciences.
dc.date.issued2017
dc.description1 ethesis (xiv, 183 pages) :
dc.descriptionillustrations, charts (some colour)
dc.descriptionIncludes bibliographical references (pages 161-183)
dc.description.abstractTransactional data such as shopping logs, web search queries, and medical notes present enormous opportunities for knowledge discovery through data mining. When such data is published for knowledge discovery however, privacy disclosure risks may arise, making privacy preserving publication a fundamental requirement. While most existing solutions for the privacy preserving publication problem are geared towards structured relational data,very few focus on unstructured data, particularly transactional data. This work explores the existing privacy preserving mechanisms for publishing transactional data, and develops useful and effective new publishing techniques.
dc.description.dissertationThesis (PhD(Computer and Information Science))--University of South Australia, 2017.
dc.identifier.urihttps://hdl.handle.net/11541.2/131793
dc.language.isoen
dc.provenanceCopyright 2017 Michael Bewong.
dc.subject.lcshData protection.
dc.subject.lcshManagement information systems
dc.subject.lcshTransaction systems (Computer systems)
dc.titlePrivacy preserving publication of transactional data /
dc.typethesis
dcterms.accessRights506 0#$fstar $2Unrestricted online access
ror.fileinfo12160028160001831 13160028150001831 Bewong, Michael - Redacted Thesis
ror.mmsid9916192110401831

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