Optimization Through Bayesian Classification on the k-Anonymized Data

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Provided by: Interscience Open Access Journals
Topic: Security
Format: PDF
Privacy preserving in data mining & publishing, plays a major role in today networked world. It is important to preserve the privacy of the vital information corresponding to a data set. This process can be achieved by k-anonymization solution for classification. Along with the privacy preserving using anonymization, yielding the optimized data sets is also of equal importance with a cost effective approach. In this paper top-down refinement algorithm has been proposed which yields optimum results in a cost effective manner.
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