Semantic similarity between terms for query suggestion

To retrieve semantically related documents with the query submitted by the user has always become a challenging task. An efficient assessment of semantic similarity is of critical importance in the area of information retrieval and web mining so as to associate the query with its associated documents. However their cannot be any accurate measure for semantic similarity as its domain is spread not only over individual words but also on the terms, phrases, sentences, entity and sometime even over whole of the document. To calculate semantic similarity between terms based on synsets a new method is proposed in this paper in which synsets are derived using online resources. The advantage of the proposed work is that, the semantic similarity between terms is calculated that helps in query suggestion or replacement of one query with the most appropriate query.

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