Chapter 7. Scalable and Privacy Preserving Distributed Data Analysis Over a Service-Oriented Platform

  1. Werner Dubitzky
  1. William K. Cheung

Published Online: 22 JUN 2009

DOI: 10.1002/9780470699904.ch7

Data Mining Techniques in Grid Computing Environments

Data Mining Techniques in Grid Computing Environments

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

  1. Biomedical Sciences Research Institute, University of Ulster, Coleraine, United Kingdom

Author Information

  1. Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong

Publication History

  1. Published Online: 22 JUN 2009
  2. Published Print: 14 NOV 2008

ISBN Information

Print ISBN: 9780470512586

Online ISBN: 9780470699904

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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