A heuristic data reduction approach for associative classification rule hiding
When data are to be shared between business partners, there could be some sensitive patterns which should not be disclosed to the other parties. On the other hand, the "quality" of the data must also be preserved. This creates an interesting question: how can we maintain the shared data th...
Saved in:
Main Authors: | Juggapong Natwichai, Xingzhi Sun, Xue Li |
---|---|
Format: | Book Series |
Published: |
2018
|
Subjects: | |
Online Access: | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=58349098012&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/60281 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Chiang Mai University |
Similar Items
-
Data reduction approach for sensitive associative classification rule hiding
by: Juggapong Natwichai, et al.
Published: (2018) -
Associative classification rules hiding for privacy preservation
by: Juggapong Natwichai, et al.
Published: (2018) -
A heuristic data reduction approach for associative classification rule hiding
by: Natwichai J., et al.
Published: (2014) -
Data quality in privacy preservation for associative classification
by: Nattapon Harnsamut, et al.
Published: (2018) -
A novel heuristic algorithm for privacy preserving of associative classification
by: Nattapon Harnsamut, et al.
Published: (2018)