Integrating Ontology Learning and R for Providing Services Efficiently in Cities

With the advancement in Artificial Intelligence, Intelligent systems are being implemented that are able to perform cognitive functions like human beings but due to the complexity in this domain and lack of measure of semantics in program, it is difficult to analyze that how these functions are performed, what functions are to be considered, to what degree they are to be considered. As ontology has been proven the excellent mean of providing semanticity, definitions that are machine understandable are created through ontology. The purpose of creating knowledge representation through ontology that is to analyze the data related to urban services. In this way, intelligent systems will use the definitions created through ontology for doing analysis. This is to be done to provide services in cities in a better way. This paper deals with the learning of base ontology in specific domain from a relational database by making use of plug-in available in Protege. By populating the ontology through learning, functions available in R will be used to remove the redundant/implied ontological terms. This will evaluate/curate the ontology.