Inter Word Semantic and String Distance Using Ontological Techniques

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 overlappingparts. Forthisreasonontologiesneedtobebroughtintomutualagreement (aligned). Thusontologymatchingbetweenwordsisausefultechniquefordataintegrationanddatasharing. Twoimportantmethodsforontologymatchingisthecomparison of words using semantic similarity and string distance metrics. In our thesis work, we haveusedalexicaldatabasecalledWordNettofindsemanticsimilaritybetweenwords. StringmetricbasedsimilarityhasbeenfoundoutbyusingJaroWinklerdistanceonthe basis of commonality and differences between two words.