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Java data mining : strategy, standard, and practice : a practical guide for architecture, design, and implementation
Abstract
Whether you are a software developer, systems architect, data analyst, or business analyst, if you want to take advantage of data mining in the development of advanced analytic applications, Java Data Mining, JDM, the new standard now implemented in core DBMS and data mining/analysis software, is a key solution component.
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This book is the essential guide to the usage of the JDM standard interface, written by contributors to the JDM standard. The book discusses and illustrates how to solve real problems using the JDM API. The authors provide you with: * Data mining introductionan overview of data mining and the problems it can address across industries; JDMs place in strategic solutions to data mining-related problems; * JDM essentialsconcepts, design approach and design issues, with detailed code examples in Java; a Web Services interface to enable JDM functionality in an SOA environment; and illustration of JDM XML Schema for JDM objects; * JDM in practicethe use of JDM from vendor implementations and approaches to customer applications, integration, and usage; impact of data mining on IT infrastructure; a how-to guide for building applications that use the JDM API. * Free, downloadable KJDM source code referenced in the book available [a href= http://www.kxen.com/products/analytic_framework/kjdm.php]here[a] * Data mining introductionan overview of data mining and the problems it can address across industries; JDM's place in strategic solutions to data mining-related problems; * JDM essentialsconcepts, design approach and design issues, with detailed code examples in Java; a Web Services interface to enable JDM functionality in an SOA environment; and illustration of JDM XML Schema for JDM objects; * JDM in practicethe use of JDM from vendor implementations and approaches to customer applications, integration, and usage; impact of data mining on IT infrastructure; a how-to guide for building applications that use the JDM API. * Free, downloadable KJDM. Source code referenced in the book available [a href= http://www.kxen.com/products/analytic_framework/kjdm.php]here[a]
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| eBook | ||
| Monografia | ||
| Description | *Java data mining : strategy, standard, and practice : a practical guide for architecture, design, and implementation / Mark F. Hornick, Erik Marcadé, Sunil Venkayala Amsterdam ; Boston : Elsevier/Morgan Kaufmann, ©2007 1 online resource (xxiv, 520 pages) : illustrations |
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| Note | English. Formato pdf/epub Accesso riservato secondo le condizioni contrattuali https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=195633 |
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| ISBN | 9786611011987 | |
| 9781281011985 | ||
| 9780080495910 | ||
| 6611011986 | ||
| 1281011983 | ||
| 0080495915 | ||
| 9780123704528 | ||
| 0123704529 | ||
| ACNP | (WASESS)SSJ0000185275 | |
| Series | The Morgan Kaufmann series in data management systems | |
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| Publication year | 2007 | |
| Contents note | Preface -- Guide to Readers -- Part I -- Strategy -- 1. Overview of Data Mining -- 2. Solving Problems in Industry -- 3. Data Mining Process -- 4. Mining Functions and Algorithms -- 5. JDM Strategy -- 6. Getting Started -- Part II -- Standard -- 7. Java Data Mining Concepts -- 8. Design of the JDM API. 9. Using the JDM API. 10. XML Schema -- 11. Web Services -- Part III -- Practice -- 12. Practical Problem Solving -- 13. Building Data Mining Tools using JDM. 14. Getting Started with JDM Web Services -- 15. Impacts on IT Infrastructure -- 16. Vendor implementations -- Part IV. Wrapping Up. 17. Evolution of Data Mining Standards -- 18. Preview of Java Data Mining 2.0. 19. Summary -- A. Further Reading -- B. Glossary |