Semantic similarity measures for IR systems using Ontology

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.