Privacy preserving Data Mining by Inverse Frequent Item Set Mining: Data Mining Approach - Couverture souple

Sawakhande, Ashwini J.

 
9786205488102: Privacy preserving Data Mining by Inverse Frequent Item Set Mining: Data Mining Approach
Couverture souple
ISBN 10 : 6205488108 ISBN 13 : 9786205488102
Editeur : LAP LAMBERT Academic Publishing, 2022

Synopsis

An emerging research topic in data mining, known as privacy-preserving data mining (PPDM) is discussed in this book. It is an application of data mining research in response to privacy security in data mining. It is called a privacy-enhanced or privacy-sensitive data mining. Preservation of privacy in data mining has emerged as an absolute prerequisite for exchanging confidential information in terms of data analysis, validation, and publishing. This book provides a panoramic overview on new perspective and systematic interpretation of a list published literature's via their meticulous organization in subcategories. The PPDM techniques can be classified based on 3 Characteristics: data distribution, purposes of hiding, Data Mining algorithms.Data mining is very important tool used by organizations for providing better service, achieving greater profit, and better decision-making. But privacy and security concerns may create barrier in data mining task. These barriers can be removed by applying PPDM techniques and by ensuring security in data mining task. Many techniques have been proposed for PPDM, with each technique having some advantages over another in its own terms.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2022
Langue
anglais
ISBN 10 
6205488108
ISBN 13 
9786205488102
Reliure
Broché
Nombre de pages
64
Coordonnées du fabricant
non disponible
Personne responsable
KreGa Onlinehandel GmbH
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