Mining Dynamic Document Spaces with Massively Parallel Embedded Processors

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


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.


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.


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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

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