The context in automatic spell correction

Automatic spell checker systems aim to verify and correct erroneous words through a suggested set of words that are the nearest lexically to the erroneous ones. However, the main disadvantage of those systems is that the wanted solution may bethe most distant lexically but the most appropriate in context. To correctly sort these solutions, the corrector must have some information about the general context of the text; the paragraph or the neighboring words of the misspelled word. In this paper, we will present an automatic spell checking method according to the context. This method is based on a learning corpus containing a distribution of the appearance probability of a word in different contexts. It combines the lexical correction via the Levenstein algorithm and the context based correction through a well definedlearning corpus which is composed of documents collected from the internet. This approach has proven efficiency and the obtained results are much more improved and satisfactory.