Privacy 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.
Reihe
Auflage
Sprache
Verlagsort
Zielgruppe
Für Beruf und Forschung
Research
Produkt-Hinweis
Fadenheftung
Gewebe-Einband
Illustrationen
20
20 s/w Abbildungen
X, 122 p. 20 illus.
Maße
Höhe: 243 mm
Breite: 164 mm
Dicke: 15 mm
Gewicht
ISBN-13
978-0-387-25886-7 (9780387258867)
DOI
10.1007/978-0-387-29489-6
Schweitzer Klassifikation
Privacy and Data Mining.- What is Privacy?.- Solution Approaches / Problems.- Predictive Modeling for Classification.- Predictive Modeling for Regression.- Finding Patterns and Rules (Association Rules).- Descriptive Modeling (Clustering, Outlier Detection).- Future Research - Problems remaining.