• DocumentCode
    2489750
  • Title

    Incremental classification of invoice documents

  • Author

    Hamza, Hatem ; Belaïd, Yolande ; Belaïd, Abdel ; Chaudhuri, Bidyut B.

  • Author_Institution
    ITESOFT
  • fYear
    2008
  • fDate
    8-11 Dec. 2008
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    This paper deals with incremental classification and its particular application to invoice classification. An improved version of an already existant incremental neural network called IGNG (incremental growing neural gas) is used for this purpose. This neural network tries to cover the space of data by adding or deleting neurons as data is fed to the system. The improved version of the IGNG, called I2GNG used local thresholds in order to create or delete neurons. Applied on invoice documents represented with graphs, I2GNG shows a recognition rate of 97.63%.
  • Keywords
    document handling; learning (artificial intelligence); neural nets; pattern classification; incremental classification; incremental growing neural gas; incremental neural network; invoice documents; Databases; Equations; Image segmentation; Machine learning; Neural networks; Neurons; Self organizing feature maps; Tree graphs;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
  • Conference_Location
    Tampa, FL
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4244-2174-9
  • Electronic_ISBN
    1051-4651
  • Type

    conf

  • DOI
    10.1109/ICPR.2008.4761832
  • Filename
    4761832