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E-Book/E-Doc
Author Hornick, Mark F.

Title Java data mining : strategy, standard, and practice : a practical guide for architecture, design, and implementation / Mark F. Hornick, Erik Marcadé, Sunil Venkayala.

Imprint Amsterdam ; Boston : Elsevier/Morgan Kaufmann, ©2007.

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Location Call No. OPAC Message Status
 Axe Elsevier ScienceDirect Ebook  Electronic Book    ---  Available
Description 1 online resource (xxiv, 520 pages) : illustrations
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
Series The Morgan Kaufmann series in data management systems
Morgan Kaufmann series in data management systems.
Bibliography Includes bibliographical references and index.
Contents 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.
Summary 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. 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].
Note Print version record.
Language English.
Subject Data mining.
Java (Computer program language)
Data Mining
Exploration de données (Informatique)
Java (Langage de programmation)
COMPUTERS -- Desktop Applications -- Databases.
COMPUTERS -- Database Management -- General.
COMPUTERS -- System Administration -- Storage & Retrieval.
Data mining
Java (Computer program language)
Genre/Form dissertations.
Academic theses
Academic theses.
Thèses et écrits académiques.
Added Author Marcadé, Erik.
Venkayala, Sunil.
Other Form: Print version: Hornick, Mark F. Java data mining. Amsterdam ; Boston : Elsevier/Morgan Kaufmann, ©2007 0123704529 9780123704528 (DLC) 2006050783 (OCoLC)72161926
ISBN 9780080495910 (electronic bk.)
0080495915 (electronic bk.)
1281011983
9781281011985
9786611011987
6611011986
0123704529
9780123704528
Standard No. (WaSeSS)ssj0000185275
AU@ 000051562770
AU@ 000054162748
CHNEW 001007067
DEBBG BV042314204
DEBBG BV043134475
DEBSZ 27524234X
DEBSZ 422200700
GBVCP 560406533
GBVCP 802324916
NZ1 11778469
NZ1 14540195
NZ1 15189251

 
    
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