Context sensitive query correction method for query-based text summarization

Abstract

Contextual spell correction is very important for real word error correction. It gives the correct word for an incorrect word in a particular sentence. The traditional spell checker can correct those misspelled words which are not present in dictionary but here we try to develop a spell checker which can give appropriate word on the basis of the contextual meaning of the sentence. This spell checker is specially applied for error correction in query-based text summarization. Here, we try to combine both semantic based measure and lexical character matching to find the appropriate word for a particular sentence.