Developing Multi-Database Mining Applications
Produktnummer:
187b017b874aa24c9a8183657ce8db5d5e
| Autor: | Adhikari, Animesh Pedrycz, Witold Ramachandrarao, Pralhad |
|---|---|
| Themengebiete: | Clustering Coding patterns Exception association rule Grouping Heavy association rule High-frequent association rule Local pattern analysis Synthesis of patterns data mining |
| Veröffentlichungsdatum: | 06.06.2010 |
| EAN: | 9781849960434 |
| Sprache: | Englisch |
| Seitenzahl: | 130 |
| Produktart: | Gebunden |
| Verlag: | Springer London |
Produktinformationen "Developing Multi-Database Mining Applications"
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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