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
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