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.
|Qualification||Doctor of Philosophy|
|Place of Publication||Australia|
|Publication status||Published - 2017|