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Java Data Mining: Strategy, Standard, and Practice
ID: 173320
Mark Hornick, Erik Marcadé, Sunil Venkayala
Whether you are a software developer, systems architect, data analyst, or business analyst, Java Data Mining, JDM, the new standard is now implemented in DBMS and data mining / analysis software, is a key solution component. This is a JDM standard interface. Written by 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; JDM's place in strategic solutions is 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; and how-to guide for use. JDM API.
* Free, downloadable KJDM source code reference in the book available here
* Data mining introduction-an overview of data mining; JDM's place in strategic solutions is 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; and how-to guide for use. JDM API.
* Free, downloadable KJDM source code reference in the book available here
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
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; JDM's place in strategic solutions is 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; and how-to guide for use. JDM API.
* Free, downloadable KJDM source code reference in the book available here
* Data mining introduction-an overview of data mining; JDM's place in strategic solutions is 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; and how-to guide for use. JDM API.
* Free, downloadable KJDM source code reference in the book available here
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
173320
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Mark Hornick, Erik Marcadé, Sunil Venkayala