EFFICIENT QUERY KEYWORD INTERPRETATION FOR SEMANTIC INFORMATION RETRIEVAL

Due to vast information available over the World Wide Web and its unstructured nature it is becoming more difficult to get relevant information. Currently, information retrieval techniques are keyword based. They do not finally capture the semantic meaning of a query keyword. To overcome this problem, conceptual knowledge to information retrieval has been introduced by means of taxonomy. In this paper, a semantic information retrieval mechanism has been presented which translates query keywords to categories belonging to a taxonomy. A hybrid similarity method has been proposed which finds the closest category corresponding to a keyword using a thesaurus like WordNet. Evaluation of the proposed approach has been done for semantic based declarative querying process which shows better results in terms of precision, recall and F-measure.