@ARTICLE{Faili, author = {Faili, Heshaam and Azadnia, Mohammad and }, title = { The First Persian Context Sensitive Spell Checker }, volume = {2}, number = {2}, abstract ={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. }, URL = {http://ijict.itrc.ac.ir/article-1-264-en.html}, eprint = {http://ijict.itrc.ac.ir/article-1-264-en.pdf}, journal = {International Journal of Information and Communication Technology Research}, doi = {}, year = {2010} }