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 A Practical Guide for architecture, design, and implementation
To order this title, and for more information, click here
By
Mark Hornick, Sr. Manager, Data Mining Technologies, Oracle Corporation, Burlington, MA
Erik Marcadé, Founder and Chief Technical Officer, KXEN, Paris, France
Sunil Venkayala, Principal Member of Technical Staff, Oracle, Burlington, MA
Description
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
Audience
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.
Contents
Preface
Guide to Readers
Part I - Strategy
1. Overview of Data Mining
1.1. Why is data mining relevant today?
1.2. Introducing Data
Mining
1.3. The Value of Data Mining
1.4. Summary
1.5. References
2. Solving Problems in Industry
2.1. Cross-industry data mining
solutions
2.2. Data Mining in Industries
2.3. Summary
2.4. References
3. Data Mining Process
3.1. A standardized data mining process
3.2. Data Analysis and Preparation?a more detailed view
3.3. Data mining modeling, analysis, and scoring processes
3.4. The Role of
databases and data warehouses in Data Mining
3.5. Data mining in enterprise software architectures
3.6. Advances in automated data
mining
3.7. Summary
3.8. References
4. Mining Functions and Algorithms
4.1. Data mining functions
4.2. Classification
4.3. Regression
4.4. Attribute Importance
4.5. Association
4.6. Clustering
4.7. Summary
4.8. References
5. JDM Strategy
5.1. What is the JDM
strategy?
5.2. Role of Standards
5.3. Summary
5.4. References
6. Getting Started
6.1. Business Understanding
6.2. Data Understanding
6.3. Data Preparation
6.4. Modeling
6.5. Evaluation
6.6. Deployment
6.7. Summary
6.8. References
Part II - Standard
7. Java
Data Mining Concepts
7.1. Classification problem
7.2. Regression problem
7.3. Attribute importance
7.4. Association rules problem
7.5. Clustering problem
7.6. Summary
7.7. References
8. Design of the JDM API
8.1. Object Modeling of Data Mining Concepts
8.2.
Modular Packages
8.3. Connection Architecture
8.4. Object Factories
8.5. URI for Datasets
8.6. Enumerated Types
8.7. Exceptions
8.8. Discovering DME Capabilities
8.9. Summary
8.10. References
9. Using the JDM API
9.1. Connection Interfaces
9.2. Using JDM
Enumerations
9.3. Using data specification interfaces
9.4. Using classification interfaces
9.5. Using Regression interfaces
9.6.
Using Attribute Importance interfaces
9.7. Using Association interfaces
9.8. Using Clustering interfaces
9.9. Summary
9.10. References
10. XML Schema
10.1. Overview
10.2. Schema Elements
10.3. Schema Types
10.4. Using PMML with the JDM Schema
10.5. Use cases for
JDM XML Schema and Documents
10.6. Summary
10.7. References
11. Web Services
11.1. What is a Web Service?
11.2. Service Oriented
Architecture (SOA)
11.3. JDM Web Service (JDMWS)
11.4. Enabling JDM Web Services using JAX-RPC
11.5. Summary
11.6. References
Part
III - Practice
12. Practical Problem Solving
12.1. Business Scenario 1: Targeted Marketing Campaign
12.2. Business Scenario 2: Understanding
Key Factors
12.3. Business Scenario 3: Using Customer Segmentation
12.4. Summary
12.5. Bibliography
13. Building Data Mining Tools
using JDM
13.1. Data mining tools
13.2. Administrative Console
13.3. User Interface to build and save a model
13.4. User Interface
to test model quality
13.5. Summary
14. Getting Started with JDM Web Services
14.1. A Web Service client in PhP
14.2. A Web Service
client in Java
14.3. Summary
14.4. References
15. Impacts on IT Infrastructure
15.1. What does Data Mining require from IT?
15.2.
Impacts on computing hardware
15.3. Impacts on data storage hardware
15.4. Data access
15.5. Backup and recovery
15.6. Scheduling
15.7. Workflow
15.8. Summary
15.9. References
16. Vendor implementations
16.1. Oracle Data Mining
16.2. KXEN (Knowledge eXtraction
ENgines)
16.3. Process for new Vendors
16.4. Process for new JDM users
16.5. Summary
16.6. References
Part IV. Wrapping Up
17.
Evolution of Data Mining Standards
17.1. Data Mining Standards
17.2. Java Community Process
17.3. Why so many standards?
17.4. Where
data mining standards have been and where will they go?
17.5. Directions for data mining standards
17.6. Summary
17.7. References
18. Preview of Java Data Mining 2.0
18.1. Transformations
18.2. Time Series
18.3. Apply for Association
18.4. Feature Extraction
18.5. Statistics
18.6. Multi-target Models
18.7. Text Mining
18.8. Summary
18.9. References
19. Summary
App. A. Further Reading
App. B. Glossary
Bibliographic & ordering Information
Paperback, 544 pages, publication date: NOV-2006
ISBN-13: 978-0-12-370452-8
ISBN-10: 0-12-370452-9
Imprint: MORGAN KAUFFMAN
Price: Order form
EUR 46.95
GBP 31.99
USD 54.95
Books and book related electronic products are priced in US dollars (USD), euro (EUR), and Great Britain Pounds (GBP). USD prices apply to the Americas and Asia Pacific. EUR prices apply in Europe and the Middle East. GBP prices apply to the UK and all other countries.
See also information about conditions of sale & ordering procedures, and links to our regional sales offices.
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Last update: 26 Aug 2008
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