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Academic Paper


Title: Correcting real-word spelling errors by restoring lexical cohesion
Author: Graeme Hirst
Email: click here TO access email
Homepage: http://www.cs.utoronto.ca/~gh/
Institution: University of Toronto
Author: Alexander Budanitsky
Institution: University of Toronto
Linguistic Field: Computational Linguistics
Abstract: Spelling errors that happen to result in a real word in the lexicon cannot be detected by a conventional spelling checker. We present a method for detecting and correcting many such errors by identifying tokens that are semantically unrelated to their context and are spelling variations of words that would be related to the context. Relatedness to context is determined by a measure of semantic distance initially proposed by Jiang and Conrath (1997). We tested the method on an artificial corpus of errors; it achieved recall of 23–50% and precision of 18–25%.

CUP AT LINGUIST

This article appears IN Natural Language Engineering Vol. 11, Issue 1, which you can READ on Cambridge's site or on LINGUIST .



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