• DocumentCode
    2470983
  • Title

    A PSO-based document classification algorithm accelerated by the CUDA Platform

  • Author

    Platos, Jan ; Snasel, Vaclav ; Jezowicz, Tomas ; Kromer, Pavel ; Abraham, Ajith

  • Author_Institution
    Dept. of Comput. Sci., VSB-Tech. Univ. of Ostrava, Ostrava, Czech Republic
  • fYear
    2012
  • fDate
    14-17 Oct. 2012
  • Firstpage
    1936
  • Lastpage
    1941
  • Abstract
    Document classification is a well-known problem that is focused on assigning predefined labels or categories to the documents found in the searched collection. Many classical algorithms were developed for solving of this problem. They usually have large time complexity and with increasing number of documents it is necessary to find algorithm which are able to find solution in reasonable time. Such algorithms are usually inspired by biological processes. Even such meta-heuristics algorithms become too slow when the number of documents is really large and it is necessary to optimize them for faster processing. This paper describes a document classification algorithm based on Particle Swarm Optimization with implementation of one and two GPUs.
  • Keywords
    document handling; graphics processing units; particle swarm optimisation; pattern classification; CUDA platform; Compute Unified Device Architecture; GPU; PSO-based document classification algorithm; biological process; graphics processing unit; metaheuristics algorithm; particle swarm optimization; searched collection; time complexity; Graphics processing units; Iris; Kernel; Particle swarm optimization; Testing; Training; Vectors; document classification; gpu; optimization; particle swarm optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics (SMC), 2012 IEEE International Conference on
  • Conference_Location
    Seoul
  • Print_ISBN
    978-1-4673-1713-9
  • Electronic_ISBN
    978-1-4673-1712-2
  • Type

    conf

  • DOI
    10.1109/ICSMC.2012.6378021
  • Filename
    6378021