An Iterative, Collaborative Ontology Construction Scheme

Nowadays, ontology of subject knowledge is applied for intelligent e-learning to provide learners with adaptive learning guidance and efficient learning content management. However, it is difficult and costly to construct an ontology for a given domain even though using the GUI tools. Therefore, how to propose an easy way to acquire the knowledge of experts, how to integrate these diverse opinions of experts into the consensus, and how to incrementally refine and converge the ontology to maintain the most suitable one have been paid attention recently. Accordingly, in this paper, we propose an Iterative, Collaborative Ontology Construction (ICOC) scheme. In each iteration, our proposed wild-like online ontology editor can help users collaboratively contribute their knowledge. Next, it automatically generates an appropriate questionnaire to converge the opinions of users to a new version of ontology using a Delphi-like method. The convergence process stops when all the relations are converged or eliminated by the questionnaire analysis. According to this ICOC scheme, the created ontology can be more acceptable.