Learning to map between ontologies on the semantic web

Ontologies play a prominent role on the Semantic Web. They make possible the widespread publication of machine understandable data, opening myriad opportunities for automated information processing. However, because of the Semantic Web's distributed nature, data on it will inevitably come from many different ontologies. Information processing across ontologies is not possible without knowing the semantic mappings between their elements. Manually finding such mappings is tedious, error-prone, and clearly not possible at the Web scale. Hence, the development of tools to assist in the ontology mapping process is crucial to the success of the Semantic Web. We describe GLUE, a system that employs machine learning techniques to find such mappings. Given two ontologies, for each concept in one ontology GLUE finds the most similar concept in the other ontology. We give well-founded probabilistic definitions to several practical similarity measures, and show that GLUE can work with all of...

• Type: Conference
• Year: 2002
• Where: WWW
• Authors: AnHai Doan, Jayant Madhavan, Pedro Domingos, Alon Y. Halevy
• Keywords: Accurate Semantic Mappings, Internet Technology, Ontology Glue, Semantic Web, WWW 2002