Java Data Mining: Strategy, Standard, and Practice: A Practical Guide for Architecture, Design, and Implementation: The Morgan Kaufmann Series in Data Management Systems
Autor Mark F. Hornick, Erik Marcadé, Sunil Venkayalaen Limba Engleză Paperback – 16 noi 2006
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Specificații
ISBN-13: 9780123704528
ISBN-10: 0123704529
Pagini: 544
Ilustrații: Approx. 110 illustrations
Dimensiuni: 191 x 235 x 25 mm
Greutate: 0.91 kg
Editura: ELSEVIER SCIENCE
Seria The Morgan Kaufmann Series in Data Management Systems
ISBN-10: 0123704529
Pagini: 544
Ilustrații: Approx. 110 illustrations
Dimensiuni: 191 x 235 x 25 mm
Greutate: 0.91 kg
Editura: ELSEVIER SCIENCE
Seria The Morgan Kaufmann Series in Data Management Systems
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Public țintă
This book is for software developers and applications architects interested in or who need data mining analysis as part of their application. It can be used by both novice and advanced java developers as a reference for incorporating data mining into applications, leveraging the sample code provided. For example, a Java developer may know he wants to classify a customer's interest in a product, but doesn't know how to get started. This book provides a quick start for using data mining in a practical context. On the other hand, experienced data miners who use Java will also gain benefits by seeing working code of how to use JSM to accomplish mining task.Cuprins
Part
I
-
Strategy1.
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 - Standard7. Java Data Mining Concepts 8. Design of the JDM API 9. Using the JDM API 10. XML Schema 11. Web Services
Part III - Practice12. 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 Up17. Evolution of Data Mining Standards 18. Preview of Java Data Mining 2.0 19. Summary
A. Further Reading B. Glossary
Part II - Standard7. Java Data Mining Concepts 8. Design of the JDM API 9. Using the JDM API 10. XML Schema 11. Web Services
Part III - Practice12. 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 Up17. Evolution of Data Mining Standards 18. Preview of Java Data Mining 2.0 19. Summary
A. Further Reading B. Glossary
Recenzii
"This
is
not
only
a
great
introduction
to
JDM,
but
also
a
great
introduction
for
a
practitioner
to
data
mining
in
general.
This
is
a
“must-have"
for
anyone
developing
large-scale
data
mining
applications
in
Java."--Robert
Grossman,
Open
Data
Group
and
University
of
Illinois
at
Chicago
"It pleases me that the Java Community ProcessSM(JCPSM) Program could host the development of the Data Mining standard, JSR 73, whose evolution and usability are presented so compellingly in Java Data Mining: Standard, Strategy, and Practice. The authors have taken a unique approach to describing a broad range of aspects from strategies to problem solving with data mining technology in a variety of industries. The book is a must-read for those who want to introduce themselves to Java data mining (JDM) and fully realize the strategic importance of this technology in an ever competitive environment."--Onno Kluyt, senior director, JCP Program at Sun Microsystems, Inc., and chair of the JCP
"Java is now ubiquitous and over the past few years the Java world has shifted focus on--among other things--new frameworks, such as the Java Data Mining (JDM) framework. JDM addresses a clear need for standardization in data mining operations, yet to those approaching both Java and data mining the mountain seems as Everest. Hornick, Marcadé, and Venkayala could not have written this book at a better time. To the expert it is reference and map of the landscape, and to the novice it will be a constant guide and companion to each journey in JDM. This book is approachable, usable, practical, and necessary for any Java data mining software architect, developer, or analyst."--Frank Byrum, Chief Scientist, CorMine Intelligent Data, LLC
"It pleases me that the Java Community ProcessSM(JCPSM) Program could host the development of the Data Mining standard, JSR 73, whose evolution and usability are presented so compellingly in Java Data Mining: Standard, Strategy, and Practice. The authors have taken a unique approach to describing a broad range of aspects from strategies to problem solving with data mining technology in a variety of industries. The book is a must-read for those who want to introduce themselves to Java data mining (JDM) and fully realize the strategic importance of this technology in an ever competitive environment."--Onno Kluyt, senior director, JCP Program at Sun Microsystems, Inc., and chair of the JCP
"Java is now ubiquitous and over the past few years the Java world has shifted focus on--among other things--new frameworks, such as the Java Data Mining (JDM) framework. JDM addresses a clear need for standardization in data mining operations, yet to those approaching both Java and data mining the mountain seems as Everest. Hornick, Marcadé, and Venkayala could not have written this book at a better time. To the expert it is reference and map of the landscape, and to the novice it will be a constant guide and companion to each journey in JDM. This book is approachable, usable, practical, and necessary for any Java data mining software architect, developer, or analyst."--Frank Byrum, Chief Scientist, CorMine Intelligent Data, LLC