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: | , |
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| 格式: | Conference or Workshop Item |
| 語言: | English |
| 出版: |
2014
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| 在線閱讀: | http://www.scopus.com/inward/record.url?eid=2-s2.0-80655143423&partnerID=40&md5=cdbbf534af0b53f8accf067bf9629cfe http://cmuir.cmu.ac.th/handle/6653943832/1538 |
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| 機構: | Chiang Mai University |
| 語言: | English |