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This work focuses on devising computational models for assessing similarity among words/concepts in the knowledge sources like ontologies.Semantic similarity assessment plays an important role in the fields of Psychology, Information Retrieval and Information Integration systems. The paradigm shift of syntactic web to semantic web has emphasized the use of development of semantic similarity measures computationally identify related concepts within and among ontologies. This work deals with semantic similarity approaches which exploit the concept relationships associated with the concepts to quantify similarity among concepts defined within and among ontologies. The work specifically is interested in proposing corpus independent information content based measures for quantifying similarity among concepts belonging to single and multiple knowledge sources.
About the author
She graduated from Pondicherry Engineering College, Puducherry, India. She completed her master's and Ph.degree from Pondicherry University, Puducherry. She joined Pondicherry Engineering College, Puducherry and has a total of 24 years teaching experience. Her research interests include ontology matching, opinion mining and information retrieval.
