Research on Ontology Integration Combined with Machine Learning

Recently ontologies are playing very important part in many areas, such as intelligent information retrieve, knowledge management and organization, electronic commerce and so on, however, several drawbacks must be overcome before ontologies become useful and practical tools. As the number of ontologies are made publicly available and accessible on the Web increases steadily, a single ontology is no longer enough to support the tasks envisaged by a distributed environment like the semantic Web. Multiple ontologies need to be accessed for several applications. A critical issue is ontology integration, which can largely improve the efficiency to enrich such a domain ontology with less time and lower cost for obtaining related knowledge. This paper has deeply studied the principles of ontology integration, then proposes a procedure model for ontology construction and a new framework for ontology integration based on machine learning through analyzing the characteristics and problems in the process of ontology integration.