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This work is licensed under a Creative Commons Attribution 4.0 International License.
Preserve Privacy of Horizontally Distributed Data through Scaling for Clustering
KHATRI NISHANT P, MS. PREETI GUPTA, TUSAL PATEL M. Tech Scholar, Computer Science and Engineering, Amity School of Engineering and Technology, Jaipur, India Computer Science and Engineering, Amity School of Engineering and Technology, Jaipur, India
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Abstract: Data sharing among organizations is considered to be useful as it offers mutual benefits for effective decision making and business growth. Data mining techniques can be applied on this shared data which can help in extracting meaningful, useful, previously unknown and ultimately comprehensible information from large databases. This paper represents a privacy preserving technique for horizontally distributed data. Procedure stated in this work is based on data matrix scaling operation.
Keywords: Data Mining, Clustering, Data Distribution, Scaling, 2D transformation
Keywords: Data Mining, Clustering, Data Distribution, Scaling, 2D transformation
How to Cite:
[1] KHATRI NISHANT P, MS. PREETI GUPTA, TUSAL PATEL M. Tech Scholar, Computer Science and Engineering, Amity School of Engineering and Technology, Jaipur, India Computer Science and Engineering, Amity School of Engineering and Technology, Jaipur, India, βPreserve Privacy of Horizontally Distributed Data through Scaling for Clustering,β International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE)
This work is licensed under a Creative Commons Attribution 4.0 International License.