|Table of Contents|

Privacy Preserving Feature Selection in Distributed Environment(PDF)

南京师范大学学报(工程技术版)[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2012年03期
Page:
60-67
Research Field:
Publishing date:

Info

Title:
Privacy Preserving Feature Selection in Distributed Environment
Author(s):
Wan WenqiangZhang Lingwei
College of Computer,Nanjing University of Posts and Telecommunications,Nanjing 210003,China
Keywords:
privacy preservingfeature selectiondistributiondifferential privacyprincipal component analysis
PACS:
TP309
DOI:
-
Abstract:
Privacy preserving and feature selection are very important in data mining. Thus,how to select feature effectively based on privacy preserving is also a hot topic. Under the Map-Reduce distributed environment framework,proposed was the combination of the differential privacy and principal component analysis with the statistics including entropy, misclassification gain,and gini index,a new privacy preserving feature selection algorithm on distributed environment. The algorithm achieved the purposes of protecting privacy of both data sets and features. The simulation results on several bench-mark data sets indicated that this algorithm performed well. During the selection of the important features, it could protect privacy information to a certain extent.

References:

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Last Update: 2013-03-11