Data quality in privacy preservation for associative classification

Privacy preserving has become an essential process for any data mining task. In general, data transformation is needed to ensure privacy preservation. Once the privacy is preserved, data quality issue must be addressed, i.e. the impact on data quality should be minimized. In this paper, k-Anonymizat...

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Bibliographic Details
Main Authors: Nattapon Harnsamut, Juggapong Natwichai, Xingzhi Sun, Xue Li
Format: Book Series
Published: 2018
Subjects:
Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=68749105788&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/60280
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Institution: Chiang Mai University
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