• DocumentCode
    295871
  • Title

    Rapid best-first retrieval from massive dictionaries by lazy evaluation of a syntactic neural network

  • Author

    Lucas, S.M.

  • Author_Institution
    Dept. of Electron. Syst. Eng., Essex Univ., Colchester, UK
  • Volume
    5
  • fYear
    1995
  • fDate
    Nov/Dec 1995
  • Firstpage
    2237
  • 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 trie-based method for large dictionaries (e.g. in excess of 100,000 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
    character recognition; neural nets; UK postcodes; lazy evaluation; massive dictionaries; rapid best-first retrieval; syntactic neural network; Associative memory; Character recognition; Content based retrieval; Dictionaries; Hidden Markov models; Information retrieval; Neural networks; Performance evaluation; Speech recognition; Systems engineering and theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1995. Proceedings., IEEE International Conference on
  • Conference_Location
    Perth, WA
  • Print_ISBN
    0-7803-2768-3
  • Type

    conf

  • DOI
    10.1109/ICNN.1995.487709
  • Filename
    487709