Comprehension and Verification of Ontology Increments via AIML and Alice Bot

Ontology construction is a repetitious and gradual operation. Involvement of both domain experts and ontologists are very important to ensure successful ontology construction. Once developed, the advantages of ontologies are numerous. However, ontology increment verification is a challenging hurdle for non-related computing domain professionals like bankers, lawyers, medical related doctors etc. Because they are not experts in resource description language (RDL) or web ontology language (OWL) specifications, semantic concepts and sparql querying. But the input of the domain specialists is very crucial in determining the adequacy and accuracy of the interpretation, presented in the specific ontology increment. Though there are existing verbalizers, almost all of them are schema and domain dependent. Therefore, tedious customizations are mandatory for using them for a new task. This is the main problem addressed in this research. As a remedy to this issue, this research attempts to resolve this technical bottleneck via a new algorithm capable of verbalizing the contents of the ontology increment in natural language, despite the domain and schema of the ontology increment. Upon testing the efficiency of the proposed algorithm for three different domain-based case experiments (i.e. law, psychology and marine biology), it yielded an overall accuracy of 82 percent.