Developing Multi-Database Mining Applications

Nonfiction, Computers, Database Management, Information Storage & Retrievel, General Computing
Cover of the book Developing Multi-Database Mining Applications by Animesh Adhikari, Pralhad Ramachandrarao, Witold Pedrycz, Springer London
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Author: Animesh Adhikari, Pralhad Ramachandrarao, Witold Pedrycz ISBN: 9781849960441
Publisher: Springer London Publication: June 14, 2010
Imprint: Springer Language: English
Author: Animesh Adhikari, Pralhad Ramachandrarao, Witold Pedrycz
ISBN: 9781849960441
Publisher: Springer London
Publication: June 14, 2010
Imprint: Springer
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

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