Developing multi database mining applications von adhikari animesh (7 Ergebnisse)
Sprache: Englisch
Verlag: Springer, 2012
Serie: Advanced Information and Knowledge Processing, Buch 24 von 66. Buch 24 von 66 - Advanced Information and Knowledge Processing
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Sprache: Englisch
Verlag: Springer, 2010
Serie: Advanced Information and Knowledge Processing, Buch 24 von 66. Buch 24 von 66 - Advanced Information and Knowledge Processing
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Zustand: New. In English.
Sprache: Englisch
Verlag: Springer-Verlag New York Inc, 2013
Serie: Advanced Information and Knowledge Processing, Buch 24 von 66. Buch 24 von 66 - Advanced Information and Knowledge Processing
- Softcover
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Weitere BilderSprache: Englisch
Verlag: Springer, 2012
Serie: Advanced Information and Knowledge Processing, Buch 24 von 66. Buch 24 von 66 - Advanced Information and Knowledge Processing
- Softcover
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Taschenbuch. Zustand: Neu. Developing Multi-Database Mining Applications | Animesh Adhikari (u. a.) | Taschenbuch | Advanced Information and Knowledge Processing | x | Englisch | 2012 | Springer | EAN 9781447125631 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartman…n[at]springer[dot]com | Anbieter: preigu.
Sprache: Englisch
Verlag: Springer, Springer, 2012
Serie: Advanced Information and Knowledge Processing, Buch 24 von 66. Buch 24 von 66 - Advanced Information and Knowledge Processing
- Softcover
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Multi-database mining is recognized as an important and strategic area of research in data mining. The authors discuss the essential issues relating to the systematic and efficient development of multi-database mining applications, and present approa…ches to the development of data warehouses at different branches, demonstrating how carefully selected multi-database mining techniques contribute to successful real-world applications. In showing and quantifying how the efficiency of a multi-database mining application can be improved by processing more patterns, the book also covers other essential design aspects. These are carefully investigated and include a determination of an appropriate multi-database mining model, how to select relevant databases, choosing an appropriate pattern synthesizing technique, representing pattern space, and constructing an efficient algorithm. The authors illustrate each of these development issues either in the context of a specific problem at hand, or via some general settings. Developing Multi-Database Mining Applications will be welcomed by practitioners, researchers and students working in the area of data mining and knowledge discovery.
Sprache: Englisch
Verlag: Springer, Springer, 2010
Serie: Advanced Information and Knowledge Processing, Buch 24 von 66. Buch 24 von 66 - Advanced Information and Knowledge Processing
- Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Multi-database mining has been recognized recently as an important and strategically essential area of research in data mining. In this book, we discuss various issues regarding the systematic and efficient development of multi-database mining applications.… It explains how systematically one could prepare data warehouses at different branches. As appropriate multi-database mining technique is essential to develop better applications. Also, the efficiency of a multi-database mining application could be improved by processing more patterns in the application. A faster algorithm could also play an important role in developing a better application. Thus the efficiency of a multi-database mining application could be enhanced by choosing an appropriate multi-database mining model, an appropriate pattern synthesizing technique, a better pattern representation technique, and an efficient algorithm for solving the problem. This book illustrates each of these issues either in the context of a specific problem, or in general. Multi-database mining is recognized as an important and strategic area of research in data mining. The authors discuss the essential issues relating to the systematic and efficient development of multi-database mining applications, and present approaches to the development of data warehouses at different branches, demonstrating how carefully selected multi-database mining techniques contribute to successful real-world applications. In showing and quantifying how the efficiency of a multi-database mining application can be improved by processing more patterns, the book also covers other essential design aspects. These are carefully investigated and include a determination of an appropriate multi-database mining model, how to select relevant databases, choosing an appropriate pattern synthesizing technique, representing pattern space, and constructing an efficient algorithm. The authors illustrate each of these development issues either in the context of a specific problem at hand, or via some general settings. Developing Multi-Database Mining Applications will be welcomed by practitioners, researchers and students working in the area of data mining and knowledge discovery.
Sprache: Englisch
Verlag: Springer London, 2010
Serie: Advanced Information and Knowledge Processing, Buch 24 von 66. Buch 24 von 66 - Advanced Information and Knowledge Processing
- Hardcover
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Zustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Multi-database mining has been recognized recently as an important and strategically essential area of research in data mining. In this book, we discuss various issues regarding the systematic and efficient development of multi-database mining applic…ations. It explains how systematically one could prepare data warehouses at different branches. As appropriate multi-database mining technique is essential to develop better applications. Also, the efficiency of a multi-database mining application could be improved by processing more patterns in the application. A faster algorithm could also play an important role in developing a better application. Thus the efficiency of a multi-database mining application could be enhanced by choosing an appropriate multi-database mining model, an appropriate pattern synthesizing technique, a better pattern representation technique, and an efficient algorithm for solving the problem. This book illustrates each of these issues either in the context of a specific problem, or in general.
