2016
DOI: 10.17485/ijst/2016/v9i3/86386
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Enhancing Privacy Preservation in Data Mining using Cluster based Greedy Method in Hierarchical Approach

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Cited by 9 publications
(4 citation statements)
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“…It assists the organization to consolidate data from different sources. In [4] developed Privacy Preservation in Data Mining using Cluster based Greedy Method for sensitive data like medical data, government, and customer care management system. Paper [5] designed Rampart framework to protect sensitive information in mined data.…”
Section: Related Workmentioning
confidence: 99%
“…It assists the organization to consolidate data from different sources. In [4] developed Privacy Preservation in Data Mining using Cluster based Greedy Method for sensitive data like medical data, government, and customer care management system. Paper [5] designed Rampart framework to protect sensitive information in mined data.…”
Section: Related Workmentioning
confidence: 99%
“…The trade-off between security and utility of data should be handled with standardizing methods for the PPDM. R. Hariharan et al [1] explained a method based on PPDM in data mining using cluster based greedy method. Application/Improvements: This method can be applied in sensitive data areas such as hospitals, Customer Management System, government survey, etc., where there is need for privacy preservation.…”
Section: Literature Surveymentioning
confidence: 99%
“…It assists the organization to consolidate data from different sources. In [4] developed Privacy Preservation in Data Mining using Cluster based Greedy Method for sensitive data like medical data, government, and customer care management system. In [5] designed Rampart framework to protect sensitive information in mined data the In [6] utilized data reduction algorithm CFS Subset and four different neural networking algorithms namely Multilayer Perception, Stochastic Gradient Descent, Logistic Regression and Voted Perception to reduce data set.…”
Section: Related Workmentioning
confidence: 99%