Building a Real Word Spell Checker based on Power Links

A context-based spelling error is a spelling or typing error that turns an intended word into another word of language. Most of the methods that tried to solve this problem were depended on the confusion sets. Confusion set are collection of words where each word in the confusion set is ambiguous with the other words in the same set. the machine learning and statistical methods depend on predefined confusion sets. In this paper, the presented method by Rokaya to define the confusion sets depending on the content and external dictionaries is adopted. A merging between this method and WinSpell to develop a refined automatic context spell checker. This method joins between the advantages of statistical and machine learning method and the re-source

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