Advertisement

Mining Dynamic Document Spaces with Massively Parallel Embedded Processors

  • Jan W. M. Jacobs
  • Rui Dai
  • Gerard J. M. Smit
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4017)

Abstract

Currently Océ investigates future document management services. One of these services is accessing dynamic document spaces, i.e. improving the access to document spaces which are frequently updated (like newsgroups). This process is rather computational intensive.

This paper describes the research conducted on software development for massively parallel processors. A prototype has been built which processes streams of information from specified newsgroups and transforms them into personal information maps.

Although this technology does speed up the training part compared to a general purpose processor implementation its real benefits emerges with larger problem dimensions because of the scalable approach.

Keywords

Winning Neuron Scalable Vector Graphic General Purpose Processor Neighbourhood Matrix Document Space 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Meij, J. (ed.): Introduction to Multidimensional Scaling. In: Dealing with the data flood. Mining data, text and multimedia. STT/Beweton, The Hague, The Netherlands (2002)Google Scholar
  2. 2.
    Perelomov, I., Azcarraga, A.P., Tan, J., Chua, T.S.: Using structured self-organizing maps in news integration websites (2002), http://citeseer.ist.psu.edu/perelomov02using.html
  3. 3.
    Skupin, A.: A cartographic approach to visualizing conference abstracts. In: IEEE Computer Graphics and Applications, pp. 50–58 (2002)Google Scholar
  4. 4.
    Jacobs, J., Bond, W., Pouls, R., Smit, G.: Colour image processing with massively parallel embedded processors. Parallel Computing (to appear, 2005)Google Scholar
  5. 5.
    Aspex Semiconductor Ltd: Linedancer - overview (2005), http://www.aspex-semi.com/pages/products/products_linedancer_overview.shtml
  6. 6.
    Duda, R., Hart, P., Stork, D.: Pattern Classification. Wiley-Interscience, Chichester (2000)Google Scholar
  7. 7.
    Kohonen, T.: Self-Organizing Maps. Springer, Heidelberg (1997)MATHGoogle Scholar
  8. 8.
    Nordstrom, T.: Designing parallel computers for self-organizing maps (1992), http://citeseer.ist.psu.edu/nordstrom92designing.html
  9. 9.
    Schikuta, E., Weidmann, C.: Data parallel simulation of self-organizing maps on hypercube architectures. In: Proceedings of WSOM 1997, Workshop on Self-Organizing Maps, Espoo, Finland, June 4-6, 1997, pp. 142–147. Helsinki University of Technology, Neural Networks Research Centre, Espoo, Finland (1997), http://citeseer.ist.psu.edu/72587.html
  10. 10.
    Wu, C.H., Hodges, R.E., Wang, C.J.: Parallelizing the self-organizing feature map on multiprocessor systems. Parallel Computing 17, 821–832 (1991)MATHCrossRefGoogle Scholar
  11. 11.
    Pohl, C., Franzmeier, M., Porrmann, M., Rückert, U.: Gnbx – reconfigurable hardware acceleration of self-organizing maps. In: Proceedings of the IEEE International Conference on Field Programmable Technology (FPT 2004), Brisbane, Australia, pp. 97–104 (2004)Google Scholar
  12. 12.
    Garcia, C., Prieto, M., Pascual-Montano, A.: A speculative parallel algorithm for self-organizing maps. Parallel Computing (to appear, 2005)Google Scholar
  13. 13.
    Krikelis, A., Weems, C.: Associative Processing and Processors. IEEE Computer Society, Los Alamitos (1997)Google Scholar
  14. 14.
    Anjewierden, A., de Hoog, R., Brussee, R., Efimova, L.: Knowledge flows in weblogs. In: Proceedings of the 13th International Conference on Conceptual Structures (ICCS 2005), Kassel, Germany (2005)Google Scholar
  15. 15.
    W3Schools: Introduction into svg (2006) [Online, accessed 12/04/2006], http://www.w3schools.com/svg/svg_intro.asp
  16. 16.
    Azcarraga, A.P., Teddy, N., Yap, J.: Extracting meaningful labels for websom text archives. In: CIKM 2001: Proceedings of the tenth international conference on Information and knowledge management, NY, USA, pp. 41–48. ACM Press, New York (2001)CrossRefGoogle Scholar
  17. 17.
    NeoMagic Corporation: The technology of associative processor array (2002), http://www.neomagic.com/product/apa_version3_1.pdf

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jan W. M. Jacobs
    • 1
  • Rui Dai
    • 2
  • Gerard J. M. Smit
    • 3
  1. 1.Océ Technologies BVVenloThe Netherlands
  2. 2.Design Technology Institute Faculty of EngineeringNational University of SingaporeSingapore
  3. 3.University of TwenteEnschedeThe Netherlands

Personalised recommendations