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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
