Java Data Mining: Strategy, Standard, & Practice (häftad)
Format
Häftad (Paperback)
Språk
Engelska
Antal sidor
520
Utgivningsdatum
2006-11-01
Upplaga
illustrated ed
Förlag
MORGAN KAUFMANN
Medarbetare
F.Hornick, Mark / Marcad, Erik / Venkayala, Sunil
Illustratör/Fotograf
110 illustrations
Illustrationer
Approx. 110 illustrations
Dimensioner
234 x 190 x 25 mm
Vikt
916 g
Antal komponenter
1
ISBN
9780123704528
Java Data Mining: Strategy, Standard, & Practice (häftad)

Java Data Mining: Strategy, Standard, & Practice

A Practical Guide for Architecture, Design, and Implementation

Häftad, Engelska, 2006-11-01
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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 introduction-an overview of data mining and the problems it can address across industries; JDM's place in strategic solutions to data mining-related problems;
* JDM essentials-concepts, 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 practice-the 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 here

* Data mining introduction-an overview of data mining and the problems it can address across industries; JDM's place in strategic solutions to data mining-related problems;
* JDM essentials-concepts, 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 practice-the 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 here
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"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, Marcad, 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

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Övrig information

Mark Hornick has lead the Java Data Mining (JSR-73) expert group since its inception in July of 2000, and now leads the JSR-247 expert group working towards JDM 2.0. Mr. Hornick brings nearly 20 years experience in the design and implementation of advanced distributed systems, including in-database data mining, distributed object management, and Java APIs. Mr. Hornick is a senior manager in Oracle's Data Mining Technologies group. Mr. Hornick joined Oracle through Oracle's acquisition of Thinking Machines Corporation in 1999. Prior to Thinking Machines, where he served as architect for TMC's next generation data mining software, Mr. Hornick was a Principal Investigator at GTE Laboratories, involved in advanced telecommunications network management software, distributed transaction management research, and distributed object management research. Mr. Hornick has contributed to several other data mining standards, including the Data Mining Group's PMML, ISO SQL/MM for Data Mining, and the Object Management Group's Common Warehouse Metadata. He has given talks at the International Conference on Knowledge Discovery and Databases, JavaOne, JavaPro Live!, and The ServerSide Symposium on data mining standards and JDM. He has also published various papers and articles over his career. Mr. Hornick holds a bachelor degree from Rutgers University in Computer Science, and a masters degree from Brown University, also in Computer science where he specialized in distributed object databases. With over 17 years of experience in the neural network industry, Erik Marcade, founder and chief technical officer for KXEN, is responsible for software development and information technologies. Prior to founding KXEN, Mr. Marcade developed real-time software expertise at Cadence Design Systems, accountable for advancing real-time software systems as well as managing "system-on-a-chip" projects. Before joining Cadence, Mr. Marcade spearheaded a project to restructure the marketing database of the largest French automobile manufacturer for Atos, a leading European information technology services company. In 1990, Mr. Marcade co-founded Mimetics, a French company that processes and sells development environment, optical character recognition (OCR) products and services using neural network technology. Prior to Mimetics, Mr. Marcade joined Thomson-CSF Weapon System Division as a software engineer and project manager working on the application of artificial intelligence for projects in weapons allocation, target detection and tracking, geo-strategic assessment, and software quality control. He contributed to the creation of Thomson Research Laboratories in Palo Alto, CA (Pacific Rim Operation-PRO) as senior software engineer. There he collaborated with Stanford University on the automatic landing and flare system for Boeing, and Kestrel Institute, a non-profit computer science research organization. He returned to France to head Esprit projects on neural networks developmen...

Innehållsförteckning

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