Automatic Spell Correction of User query with Semantic Information Retrieval and Ranking of Search Results using WordNet Approach
The proposed semantic information retrieval system handles the following : i) automatic spell correction of user query. ii) analysis and determination of the semantic feature of the content and development of a semantic pattern that represents the semantic features of the content. iii) analysis of user’s query and extension of implied semantics through semantic extension to identify more semantic features for matching. vi) generation of contents with approximate semantics by clustering the documents and matching against the extended query to provide correct contents to the querist. v) a ranking method which computes relevance of documents for actual queries by computing quantitative document–query semantic distance.
Keywords: Information retrieval, Semantic retrieval, Semantic ranking, Text retrieval, Semantic extraction, Retrieval mechanism
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