Achieving k-anonymity for associative classification in incremental-data scenarios
When a data mining model is to be developed, one of the most important issues is preserving the privacy of the input data. In this paper, we address the problem of data transformation to preserve the privacy with regard to a data mining technique, associative classification, in an incremental-data s...
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Main Authors: | Bowonsak Seisungsittisunti, Juggapong Natwichai |
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Format: | Book Series |
Published: |
2018
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Subjects: | |
Online Access: | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=80655143423&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/49867 |
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Institution: | Chiang Mai University |
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