THE FIRST PERSIAN CONTEXT SENSITIVE SPELL CHECKER
Heshaam Faili, Mohammad Azadnia · DOAJ (DOAJ: Directory of Open Access Journals) · 2010
In this article an attempt to introduce the first Persian context sensitive spell checker, which tries to detect and correct the :eat-word spelling error of Persian text is presented. The proposed method is a statistical approach which uses Bayesian framework as its probabilistic model and also uses mutual information metric as a semantic relatedness measure between different Persian words. Our experiments on sample test data, shows that accuracy of correction method is about 80% with respect to Fl-measure.