Hiding Sensitive Association Rules by Elimination Selective Item among R.H.S Items for each Selective Transaction

Lately, the significant advances in data collection, data storage technologies and also the widespread use of the World Wide Web, has led to a huge volume of data. This paper focuses on hiding sensitive association rule which is an important research problem in privacy preserving data mining. For this, the authors present an algorithm that decreases confidence of sensitive rules to below minimum threshold by removing selective item among items of consequent sensitive rule (R.H.S) for each selective transaction.

Provided by: Creative Commons Topic: Data Management Date Added: Jun 2014 Format: PDF

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