A probabilistic spellchecker

  • O. Dupin

Student thesis: Master's ThesisMaster of Science (by Research)

Abstract

This thesis studies graphical Models applied to the correction of words. More particularly, hidden Markov models and Markov chains will be used in order to build a probabilistic spellchecker. Several ways to cluster words will be introduced: the batch
K-Means clustering algorithm with a specific distance measure and the Expectation- Maximization algorithm in order to learn a mixture of Markov chains. Moreover, a
solution for dealing with the suffixes and prefixes will be presented.
Date of AwardSept 2000
Original languageEnglish
Awarding Institution
  • Aston University

Keywords

  • probabilistic
  • spell checker
  • information engineering

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