Partial multi-dividing ontology learning algorithm

The aim of the present paper is to present a partial multi-dividing ontology algorithm with the aim of obtaining an efficient approach to optimize the partial multi-dividing ontology learning model. For doing it we state several theoretical results from a statistical learning theory perspective. Moreover, we present five experiments in different engineering fields to show the precision of our partial multi-dividing algorithm from angles of ontology, similarity measuring and ontology mapping building point of view.