However, performing ontology matching automatically is an extremely difficult task. Much research has been done on this topic and the suggested approaches can be categorized as either rule-based or learning-based. The former works on ontology schema information, and the latter considers both schemas and instance data.However, manually matching ontologies is tedious work. Without help from computers, it will take a human quite a long time to match even two ontologies of moderate size, say, 50 concepts and 200 relationships each. Second, it is error- prone.
|Title||:||Towards Mutual Understanding: Rule-based and Learning-based Matching Algorithms for Ontologies|
|Publisher||:||ProQuest - 2007|