• DocumentCode
    1645740
  • Title

    Rapid searching of massive dictionaries given uncertain inputs

  • Author

    Lucas, S.M.

  • Author_Institution
    Dept. of Electron. Syst. Eng., Essex Univ., Colchester, UK
  • fYear
    1995
  • fDate
    11/2/1995 12:00:00 AM
  • Firstpage
    42705
  • Lastpage
    42712
  • Abstract
    A new method of searching large dictionaries given uncertain inputs is described, based on the lazy evaluation of a syntactic neural network (SNN). The new method is shown to significantly outperform a conventional tree-based method for large dictionaries (e.g. in excess of 100000 entries). Results are presented for the problem of recognising UK postcodes using dictionary sizes of up to 1 million entries. Most significantly, it is demonstrated that the SNN actually gets faster as more data is loaded into it
  • Keywords
    algorithm theory; neural nets; optical character recognition; pattern recognition; postal services; search problems; England; Great Britain; UK postcode; content addressable memory; fuzzy data retrieval; large dictionaries; lazy evaluation; massive dictionary; neural net; postal service; rapid searching; search strategy; syntactic neural network; uncertain input; uncertain inputs;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Document Image Processing and Multimedia Environments, IEE Colloquium on
  • Conference_Location
    London
  • Type

    conf

  • DOI
    10.1049/ic:19951193
  • Filename
    498885