Efficient Detection of Duplicate Data using Progressive Techniques

International Journal of Communication and Media Science

© 2016 by SSRG - IJCMS Journal

Volume 3 Issue 3

Year of Publication : 2016

Authors : M.Anusuya and R.Kiruba Kumari

10.14445/2349641X/IJCMS-V3I5P101

How to Cite?

M.Anusuya and R.Kiruba Kumari, "Efficient Detection of Duplicate Data using Progressive Techniques," SSRG International Journal of Communication and Media Science, vol. 3,  no. 3, pp. 1-5, 2016. Crossref, https://doi.org/10.14445/2349641X/IJCMS-V3I5P101

Abstract:

 Privacy Preserving Data Mining Systems is to propose local data mining and global data mining. It attempts to benefit of extracting useful information from large volumes of data. Privacy-preserving data mining usually has multiple steps that translate to a three-tiered architecture. Online data collection systems are an example of new applications that threaten individual privacy. Already companies are sharing data mining models to obtain a richer set of data about mutual customers and their buying habits as Data Providers, Data Warehouse Server and Data Mining server. Our goal in investigating privacy preservation issues was to take a systemic view of architectural requirements and design principles and explore possible solutions that would lead to guidelines for building practical privacy preserving Central to the strategy are three protocols that govern privacy disclosure among entities as Data collection protocol, Inference Control Protocol and Information sharing Protocol.

Keywords:

   Privacy Preserving, Inference Control Protocol, Data Warehouse, Investigating.

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