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DMKD
2004
ACM

Mining association rules with non-uniform privacy concerns

11 years 11 months ago
Mining association rules with non-uniform privacy concerns
Privacy concerns have become an important issue in data mining. A popular way to preserve privacy is to randomize the dataset to be mined in a systematic way and mine the randomized dataset instead. On the other hand, people usually have different privacy concerns for different attributes in data. E.g., in survey data, the sensitivity of questions varies. Appropriate use of this information can lead to more accurate data mining results. However, this information has not been fully utilized by many privacy preserving association rule mining algorithms. In this paper, we generalize the privacy preserving association rule mining problem by allowing different attributes to have different levels of privacy, that is, using different randomization factors for values of different attributes in the randomization process. We also propose an efficient algorithm RE (Recursive Estimation) to estimate the support of itemsets under this framework. Both theoretical and empirical results show th...
Yi Xia, Yirong Yang, Yun Chi
Added 30 Jun 2010
Updated 30 Jun 2010
Type Conference
Year 2004
Where DMKD
Authors Yi Xia, Yirong Yang, Yun Chi
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