Developing Distributed Data Mining Applications in the Knowledge Grid Framework

  • Giuseppe Bueti
  • Antonio Congiusta
  • Domenico Talia
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3402)

Abstract

The development of data intensive and knowledge-based applications on Grids is a research area that today is receiving significant attention. One of the main topics in that area is the implementation of distributed data mining applications using Grid computing services and distributed resource management facilities. This paper describes the development process of distributed data mining applications on Grids by using the KNOWLEDGE GRID framework. After a quick introduction to the system principles and a description of tools and services it offers to users, the paper describes the design and implementation of two distributed data mining applications by using the KNOWLEDGE GRID features and tools and gives experimental results obtained by running the designed applications on real Grids.

Keywords

Grid Computing Data Processing Data Mining 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Alcamo, P., Domenichini, F., Turini, F.: An XML based environment in support of the overall KDD process. In: Proc. 4th Intl. Conference on Flexible Query Answering Systems, pp. 413–424. Physica-Verlag, Heidelberg (2000)Google Scholar
  2. 2.
    Cannataro, M., Talia, D.: The Knowledge Grid. Communications of the ACM 46(1), 89–93 (2003)CrossRefGoogle Scholar
  3. 3.
    Cannataro, M., Congiusta, A., Talia, D., Trunfio, P.: A Data Mining Toolset for Distributed High-Performance Platforms. In: Proc. 3rd Intl. Conference Data Mining 2002, Bologna, Italy, pp. 41–50. WIT Press, Southampton (2002)Google Scholar
  4. 4.
    Foster, I., Kesselman, C., Tuecke, S.: The Anatomy of the Grid: Enabling Scalable Virtual Organizations. Intl. Journal of Supercomputer Applications 15(3) (2001)Google Scholar
  5. 5.
    Kargupta, H., Joshi, A., Sivakumar, K., Yesha, Y. (eds.): Data Mining: Next Generation Challenges and Future Directions. MIT/AAAI Press (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Giuseppe Bueti
    • 1
  • Antonio Congiusta
    • 1
  • Domenico Talia
    • 1
  1. 1.DEISUniversity of CalabriaRende (CS)Italy

Personalised recommendations