Privacy preserving publication of transactional data /

Date

2017

Authors

Bewong. Michael,

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thesis

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Abstract

Transactional 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.

School/Discipline

University of South Australia. School of Information Technology and Mathematical Sciences.
School of Information Technology and Mathematical Sciences.

Dissertation Note

Thesis (PhD(Computer and Information Science))--University of South Australia, 2017.

Provenance

Copyright 2017 Michael Bewong.

Description

1 ethesis (xiv, 183 pages) :
illustrations, charts (some colour)
Includes bibliographical references (pages 161-183)

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506 0#$fstar $2Unrestricted online access

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