Enhanced Expressivity using Deontic Logic and Reuse Measure of Ontologies

Measuring and aligning ontologies is the only remedy of ontology sharing and reuse. The management of the less expressive target ontology is a complicated problem and such reduced expressivity often occurs due to poor implicit semantic knowledge representation and the use of polymorphic objects. Efficient sharing and reuse of knowledge is achieved by providing enhanced expressivity by uncovering the implicit knowledge of the target domain and the detection of erasure of polymorphic objects. This paper uses deontic logic based Graph Derivation Representation approach in order to provide enhanced expressivity of the target ontologies. Distance based similarity metric is used in the proposed framework for the purpose of ontology reuse. The proposed framework is implemented on several web datasets which shows the efficiency of the underlying algorithm. The effectiveness of the experimental results is promising when compared to other Graph Derivation Representation methods that are evident from the illustrated graphical results.