Science & Engineering Research Support soCiety (SERSC)
In this paper the authors propose an ontology learning and population model from structured data sources. Recently various attempts have been made to harmonize web 2.0 and the semantic web, named as web 3.0 or web 4.0. One of the most important issues for realization of the next web platform is about how to make web ontology rich as well as to address semantic interoperability between ontologies. To resolve those issues, web ontology schemas should be precisely defined in semantic aspect and they should also develop a method for learning and population of ontology instances from diverse resources.