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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xiaolin Zhang Hongjing Bi |
| Copyright Year | 2010 |
| Description | Author affiliation: Department of Computer Science, Tangshan Normal University, China (Hongjing Bi) || School of Information and Engineering, Inner Mongolia University of Science and Technology, Baotou, China (Xiaolin Zhang) |
| Abstract | With the extending of the data mining application domain, the research of the privacy preserving data mining technique becomes more and more important. Privacy preserving classified data mining which is the main type of the privacy protection data mining has already become one of the hot spots in the field of data mining in recent years. How to transform the primitive real data and then structure decision tree based on the transformed data set is the key point of the privacy preserving classified data mining. This paper proposes a kind of privacy preserving classification mining method which is based on the random perturbation matrix. This method is suitable to the data of the character type, the boolean type, the classified type and the digital type. The experimental results show that our method protects privacy adequately and has high accuracy in the mining results. |
| File Size | 461535 |
| File Format | |
| ISBN | 9781424481040 |
| e-ISBN | 9781424481064 |
| DOI | 10.1109/ICINA.2010.5636410 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-10-18 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Data privacy Random perturbation matrix Bismuth Electrocardiography Encoding Privacy preserving Cardiology Data mining Decision tree |
| Content Type | Text |
| Resource Type | Article |
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