Research on domain ontology in different granulations based on concept lattice

This paper introduces concept lattice and granular computing into ontology learning, and presents a unified research model for ontology building, ontology merging and ontology connection based on the domain ontology base in different granulations. In this model, as the knowledge in the lowest and most basic level, the domain ontology base is presented firstly, which provides a uniform technology for ontology learning on the whole; secondly, in order to better understand problems rather than be overwhelmed unnecessary details, granular computing is introduced to abstract and simplify domain ontology bases in complex domains. Moreover, the similarly of concepts in different granulations is introduced to help domain experts judging relations except for inheritance relation, and the similarity of ontologies in multi-granulations is introduced to measure the degree of connection of ontologies; finally, based on similarity models mentioned above, the ontology building, ontology merging and ontology connection can be obtained in different granulations with the help of domain experts. It is shown by instances that the application of the model presented in this paper is valid and practicable. Although there are still some problems in applications of this model (for example, ontology learning cannot dispense with the intervention of domain experts yet), this paper offers a new way for combining ontology learning and concept lattice.