Our approach draws on previous research in English spelling and query correction, Japanese katakana variation and transliteration, and semantic similarity, and builds a model that makes improvements over previously proposed query correction methods.
the use of orthographically augmented semantic kernels proposed in this paper is general and applicable to other languages, including English, for query alteration, especially when the data sparseness is an issue.