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
Link To Document :
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