陳怡燕

Knowledge influences the competition of organizations crucially. Because of knowledge changing and updating frequently, knowledge engineers need to get knowledge from different sources. Therefore, it is important to integrate relative domain knowledge to support users applying, sharing and reusing knowledge. However, knowledge is an abstract concept which is difficult to define and not easy to integrate. 　　Ontology is an explicit specification of a conceptualization and could share common understanding of the structure of knowledge. It is popular among knowledge engineering domain. Even though ontology could represent knowledge model, it still exits lots of semantic or structure mismatches. Therefore, the core of knowledge integration is ontology integration. 　　An ontology-based knowledge integration mechanism is proposed in this research, including an ontology mapping model and an ontology similarity computing algorithm. This mechanism finds semantic similarity among ontologies and map same concepts between different ontologies automatically to achieve ontology integration. 　　Besides class names and properties of ontology, the “internal-relations” is used as the mapping criteria in this research to get better results of ontology mapping. The integrated ontology achieves knowledge integration, improves system interoperability, and constructs a more robust semantic web to facilitate knowledge searching and reasoning.