Distributed Data Mining in the Grid Environment

  • C. B. SelvaLakshmi
  • S. Murali
  • P. Chanthiya
  • P. N. Karthikayan
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 216)

Abstract

Grid computing has emerged as an important new branch of distributed computing focused on large-scale resource sharing and high-performance orientation. In many applications, it is necessary to perform the analysis of very large data sets. The data are often large, geographically distributed and its complexity is increasing. In these areas, grid technologies provide effective computational support for applications such as knowledge discovery. This paper is an introduction to grid infrastructure and its potential for machine learning tasks.

Keywords

Grid computing Knowledge grid Data mining Distributed data mining 

References

  1. 1.
    Berman, F.: From Teragrid to Knowledge Grid. Commun. ACM. 44(11), 27–28 (2001)CrossRefGoogle Scholar
  2. 2.
    Cannataro, M., Talia, D.: The knowledge grid. Commun. ACM. 46(1), 89–93 (2003)CrossRefGoogle Scholar
  3. 3.
    Foster, I., Kesselman, C., Nick, J., Tuecke, S. The physiology of the grid. In: Berman, F., Fox, G., Hey, A. (eds.) Grid Computing: Making the Global Infrastructure a Reality, pp. 217–249. Wiley (2003) Google Scholar
  4. 4.
    Czajkowski, K. et al. The WS-Resource Framework Version 1.0. http://www-106.ibm.com/developerworks/library/ws-resource/wswsrf.pdf
  5. 5.
    Witten, H., Frank, E. Data Mining: Practical Machine Learning Tools with Java Implementations. Morgan KaufmannGoogle Scholar
  6. 6.
    Talia, D., Trunfio, P., Verta, O. Weka4WS: a WSRFenabled Weka toolkit for distributed data mining on grids. In Proceedings of PKDD 2005, LNAI vol. 3721, pp. 309–320. Springer-Verlag, Porto, Portugal, October (2005)Google Scholar
  7. 7.
    Cannataro, M., Congiusta, A., Mastroianni, C., Pugliese, A., Talia, D., Trunfio, P.: Grid-based data mining and knowledge discovery. In: Zhong, N., Liu, J. (eds.) Intelligent Technologies for Information Analysis, pp. 19–45. Springer-Verlag, (2004)Google Scholar
  8. 8.
    Cannataro, M., Talia, D.: Semantics and knowledge grids: building the next generation grid. IEEE Intell. Syst. 19(1), 56–63 (2004)CrossRefGoogle Scholar
  9. 9.
    Kargupta, H., Kamath, C., Chan, P. Distributed and parallel data mining: emergence, growth, and future directions, In: Advances in Distributed and Parallel Knowledge Discovery, pp. 409–416. AAAI/MIT Press (2000) Google Scholar

Copyright information

© Springer India 2014

Authors and Affiliations

  • C. B. SelvaLakshmi
    • 1
  • S. Murali
    • 1
  • P. Chanthiya
    • 1
  • P. N. Karthikayan
    • 1
  1. 1.Velammal College of Engineering and TechnologyMaduraiIndia

Personalised recommendations