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Text Analysis and Correction Using Specialized Linguistic Habit Graphs LHG

Abstract This paper introduces a novel linguistic habit graph LHG for automation of contextual text correction. The result of our current researches is a constructed mechanism for searching and aggregating tens of millions word-triples from websites that create a simple context statement for a given language that makes us able to predict word sequences and proceed corrections better than currently used solutions. Moreover, the LHG graph during colleting word-triples grow is limited and slows down so LHG graphs can be continuously supplemented by reading next texts to improve the correction results.