Privacy preserving Data Mining by Inverse Frequent Item Set Mining: Data Mining Approach - Softcover
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.
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Privacy preserving Data Mining by Inverse Frequent Item Set Mining: Data Mining Approach
Published by
LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6205488108
ISBN 13: 9786205488102
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Softcover
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Privacy preserving Data Mining by Inverse Frequent Item Set Mining: Data Mining Approach
Published by
LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6205488108
ISBN 13: 9786205488102
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Softcover
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Privacy preserving Data Mining by Inverse Frequent Item Set Mining
Published by
LAP LAMBERT Academic Publishing Aug 2022, 2022
ISBN 10: 6205488108
ISBN 13: 9786205488102
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 64 pp. Englisch. Seller Inventory # 9786205488102
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Privacy preserving Data Mining by Inverse Frequent Item Set Mining: Data Mining Approach
Published by
LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6205488108
ISBN 13: 9786205488102
New
Softcover
Seller: Biblios, Frankfurt am main, HESSE, Germany
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Privacy preserving Data Mining by Inverse Frequent Item Set Mining
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LAP Lambert Academic Publishing, 2022
ISBN 10: 6205488108
ISBN 13: 9786205488102
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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-sens. Seller Inventory # 699354112
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Privacy preserving Data Mining by Inverse Frequent Item Set Mining
Published by
LAP LAMBERT Academic Publishing Aug 2022, 2022
ISBN 10: 6205488108
ISBN 13: 9786205488102
New
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Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch. Seller Inventory # 9786205488102
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Privacy preserving Data Mining by Inverse Frequent Item Set Mining : Data Mining Approach
Published by
LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6205488108
ISBN 13: 9786205488102
New
Taschenbuch
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Seller Inventory # 9786205488102
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Privacy preserving Data Mining by Inverse Frequent Item Set Mining | Data Mining Approach
Published by
LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6205488108
ISBN 13: 9786205488102
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Taschenbuch
Seller: preigu, Osnabrück, Germany
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Taschenbuch. Condition: Neu. Privacy preserving Data Mining by Inverse Frequent Item Set Mining | Data Mining Approach | Ashwini J. Sawakhande | Taschenbuch | Englisch | 2022 | LAP LAMBERT Academic Publishing | EAN 9786205488102 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 123946328