Chapter 7. Scalable and Privacy Preserving Distributed Data Analysis Over a Service-Oriented Platform
- Werner Dubitzky
Published Online: 22 JUN 2009
DOI: 10.1002/9780470699904.ch7
Copyright © 2008 John Wiley & Sons, Ltd
Book Title
Data Mining Techniques in Grid Computing Environments
Additional Information
How to Cite
Cheung, W. K. (2009) Scalable and Privacy Preserving Distributed Data Analysis Over a Service-Oriented Platform, in Data Mining Techniques in Grid Computing Environments (ed W. Dubitzky), John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9780470699904.ch7
Editor Information
Biomedical Sciences Research Institute, University of Ulster, Coleraine, United Kingdom
Publication History
- Published Online: 22 JUN 2009
- Published Print: 14 NOV 2008
ISBN Information
Print ISBN: 9780470512586
Online ISBN: 9780470699904
- Summary
- Chapter
Keywords:
- scalability and data privacy;
- data analysis challenges;
- scalable and privacy preserving data mining paradigm;
- Business Process Execution Language (BPEL);
- Gaussian mixture model (GMM);
- modelling distributed data mining and workflow processes;
- Extensible Stylesheet Language Transformation (XSLT);
- BPEL process creation tools - Oracle BPEL designer or ActiveBPEL
Summary
This chapter contains sections titled:
Introduction
A service-oriented solution
Background
Model-based scalable, privacy preserving, distributed data analysis
Modelling distributed data mining and workflow processes
Lessons learned
Further research directions
Conclusions
References