An algorithm for finding document concepts using semantic similarities from WordNet ontology Online publication date: Sun, 17-Oct-2010
by Aditi Sharan, Manju L. Joshi
International Journal of Computational Vision and Robotics (IJCVR), Vol. 1, No. 2, 2010
Abstract: Semantic similarity is becoming a generic issue in a variety of applications in area of information retrieval (IR). Most of the researchers are using ontology as a tool for finding semantic similarities. Use of ontology allows terms in documents to be replaced by the concepts. The concepts are generally selected by identifying semantically related terms and finding a suitable term (concept) to replace them. Several approaches have been proposed for finding concepts by selecting semantically related terms, however no attempt has been made to automatise the process. The motivation of this paper is to suggest an automatic method of identifying the concepts from documents using hypernym relationship in ontologies and propose an algorithm for the same. WordNet ontology has been used for implementing the algorithm. The algorithm can be used for finding document concepts and clustering the documents based on these concepts.
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