Home
This Title All WIREs
WIREs RSS Feed
How to cite this WIREs title:
WIREs Data Mining Knowl Discov
Impact Factor: 2.111

Association rule hiding methods

Full article on Wiley Online Library:   HTML PDF

Can't access this content? Tell your librarian.

Privacy preserving data mining has been recently introduced to cope with privacy issues related to the data subjects in the course of the mining of the data. It has also been recognized that it is not only the data that need to be protected but sensitive knowledge hidden in the data as well. Knowledge hiding is an emerging area of research focusing on appropriately modifying the data in such a way that sensitive knowledge escapes the mining and is not communicated to the public for privacy purposes. This article investigates the development of techniques falling under the knowledge‐hiding umbrella that pertain to the association rule‐mining task. These techniques are known as association rule hiding or frequent pattern hiding approaches, and have been receiving a lot of attention lately because they touch upon important issues of handling a sort of commonly used patterns such as the frequent patterns and the association rules. We present an overview of this area as well as a taxonomy and a presentation of an important sample of algorithms. © 2013 Wiley Periodicals, Inc.

Browse by Topic

Algorithmic Development > Association Rules
Technologies > Association Rules

Access to this WIREs title is by subscription only.

Recommend to Your
Librarian Now!

The latest WIREs articles in your inbox

Sign Up for Article Alerts