Abstract:
Ontologies are today a key part of every knowledge based system. They provide a source of shared and precisely defined terms, resulting in system interoperability by knowledge sharing and reuse. Unfortunately, the variety of ways that a domain can be conceptualized results in the creation of different ontologies with contradicting or overlapping parts. For this reason ontologies need to be brought into mutual agreement (aligned). Thusontologymatchingbetweenwordsisausefultechniquefordataintegrationanddatasharing. Two important methods for ontology matching is the comparison of words using semantic similarity and string distance metrics. In our thesis work, we have use dalexical database called WordNet to find semantic similarity between words. StringmetricbasedsimilarityhasbeenfoundoutbyusingJaroWinklerdistanceonthe basis of commonality and differences between two words.
