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Java Data Mining: Strategy, Standard, and Practice, By Mark F. Hornick, Erik Marcad� and Sunil Venkayala

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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

ISBN: 978-0-12-370452-8
November 2006, Paperback, 544 Pages
List Price: $49.95

Java Data Mining (JDM), the new standard implemented in core DBMSs and data mining/analysis software, is the key solution for those who want to take advantage of data mining in the development of advanced analytic applications. Java Data Mining: Strategy, Standard, and Practice is the essential guide to the usage of the JDM standard interface. This reference will help you produce applications with advanced analytics and predictive analytic capabilities, and it is the first and authoritative guide to JDM, 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: o An overview of data mining and JDM's place in strategic solutions to data mining-related problems; o JDM's essentials-the design approach and design issues, with detailed code examples; a Web Services interface to enable JDM functionality in an SOA environment; and illustration of JDM XML Schema for JDM objects; o 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. Here, we illustrate how to build applications that use the JDM API.

Table of 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