Ontology learning in Citespace and OntoGen

Ontology is a formal explicit specification of a domain. Supported by ontology, domain concepts can be explicitly described. In addition, both the user and the system can communicate with each other using a common understanding of a domain. In recent years, the acquisition of ontologies from domain texts using machine learning and text mining methods has been proposed as a means of facilitating the ontology engineering process. These ontology learning tools not only make ontology construction cheaper and faster, but also make it possible to change from knowledge acquisition in ontology learning into data-driven acquisition. In this study, the author applies NSF awards data to compare two ontology learning tools, CiteSpace and OntoGen from four aspects: data requirement, data analysis, visualization and ontology learning ability. The comparison covers the main research domains of ontology learning, and it gives suggestion for future ontology learning