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Hornick / Marcade / Venkayala

Java Data Mining: Strategy, Standard, and Practice

Medium: Buch
ISBN: 978-0-12-370452-8
Verlag: MORGAN KAUFMANN PUBL INC
Erscheinungstermin: 17.11.2006
Lieferfrist: bis zu 10 Tage
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.


- 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

Produkteigenschaften


  • Artikelnummer: 9780123704528
  • Medium: Buch
  • ISBN: 978-0-12-370452-8
  • Verlag: MORGAN KAUFMANN PUBL INC
  • Erscheinungstermin: 17.11.2006
  • Sprache(n): Englisch
  • Auflage: Erscheinungsjahr 2006
  • Serie: Morgan Kaufmann Series in Data
  • Produktform: Kartoniert
  • Gewicht: 907 g
  • Seiten: 544
  • Format (B x H x T): 189 x 235 x 25 mm
  • Ausgabetyp: Kein, Unbekannt

Autoren/Hrsg.

Autoren

Hornick, Mark F.

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.

Marcade, Erik

Venkayala, Sunil

J2EE and XML group leader and Principal Member of Technical Staff at Oracle Data Mining Technologies. Expert group member of Java Data Mining (JDM) standard developed under JSR-73. More than five years experience in developing applications using predictive technologies available in the Oracle Database. More than seven years of experience in working with Java and Internet technologies. Authored JDM article in Java Developer Journal. Holds a B.S in Engineering and Masters in Industrial Management from Indian Institute Of Technology, Kanpur.

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