Exploiting Ontology for Concept Based Information Retrieval

Traditional approaches for information retrieval from textual documents are based on keyword based similarity. A key limitation of these approaches is that they do not take care of meaning and semantic relationship between words. Recently some work has been done on concept based information retrieval(CBIR), which allows to capture semantic relations between words in order to identify importance of a word. These semantic relations can be explored by using ontology. Most of the work for CBIR has been done in English language. In this paper we explore the use of Hindi Wordnet ontology for CBIR from Hindi text documents. Our work is significant because very limited amount of work has been done on CBIR for Hindi documents. Basic motivation of this paper is to provide an efficient structure for representing concept clusters and develop an algorithm for identifying concept clusters. Further we suggest a way of assigning weights to words based on their semantic importance in the document.