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A novel binary spell checker

By V.J. Hodge and J. Austin

Abstract

In this paper we propose a simple, flexible and efficient hybrid spell checking methodology based upon phonetic matching, supervised learning and associative matching in the AURA neural system. We evaluate our approach against several benchmark spell-checking algorithms for recall accuracy. Our proposed hybrid methodology has the joint highest top 10 recall rate of the techniques evaluated. The method has a high recall rate and low computational cost

Publisher: Springer-verlag
Year: 2001
OAI identifier: oai:eprints.whiterose.ac.uk:775

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