Rapid best-first retrieval from massive dictionaries (paper available)

[Simon Lucas]

The following paper has recently been published in Pattern
Recognition Letters (vol 17; 1507 - 1512), and may be
of interest to people on this list.


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Rapid Best-First Retrieval from Massive Dictionaries
by Lazy Evaluation of a Syntactic Neural Network
S.M. Lucas


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 {\em faster} as more data
is loaded into it.
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Sorry, but no electronic version available due to
copyright.  Paper offprints available on request.

 Regards,

   Simon Lucas



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Dr. Simon Lucas
Department of Electronic Systems Engineering
University of Essex
Colchester CO4 3SQ
United Kingdom

Tel:    (+44) 1206 872935
Fax:    (+44) 1206 872900
Email:  sml at essex.ac.uk
http://esewww.essex.ac.uk/~sml
secretary:  Mrs Janet George  (+44) 1206 872438
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