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OverviewPrivacy preserving data mining implies the mining of knowledge from distributed data without violating the privacy of the individual/corporations involved in contributing the data. This volume provides a comprehensive overview of available approaches, techniques and open problems in privacy preserving data mining. Crystallizing much of the underlying foundation, the book aims to inspire further research in this new and growing area. Privacy Preserving Data Mining is intended to be accessible to industry practitioners and policy makers, to help inform future decision making and legislation, and to serve as a useful technical reference. Full Product DetailsAuthor: Jaideep Vaidya , Chris Clifton , Michael ZhuPublisher: Springer Imprint: Springer Volume: 39 Dimensions: Width: 23.40cm , Height: 0.70cm , Length: 15.60cm Weight: 0.200kg ISBN: 9780387507217ISBN 10: 0387507213 Pages: 266 Publication Date: 01 January 1989 Audience: General/trade , General Format: Undefined Publisher's Status: Unknown Availability: Out of stock ![]() Table of ContentsReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |