Abstract
Information retrieval (IR) is the area of study concerned with searching documents or information within documents. The user describes information needs with a query which consists of a number of words. Finding weight of a query term is useful to determine the importance of a query. Calculating term importance is fundamental aspect of most information retrieval approaches and it is traditionally determined through Term Frequency -Inverse Document Frequency (IDF). This paper proposes a new term weighting technique called concept-based term weighting (CBW) to give a weight for each query term to determine its significance by using WordNet Ontology. General Terms Term frequency (TF), Inverse Document Frequency (IDF), Vector Space Model, Extraction Algorithm.
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