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Learning to match ontologies on the Semantic Web

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Abstract.

On the Semantic Web, data will inevitably come from many different ontologies, and information processing across ontologies is not possible without knowing the semantic mappings between them. Manually finding such mappings is tedious, error-prone, and clearly not possible on 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 them. Another key feature of GLUE is that it uses multiple learning strategies, each of which exploits well a different type of information either in the data instances or in the taxonomic structure of the ontologies. To further improve matching accuracy, we extend GLUE to incorporate commonsense knowledge and domain constraints into the matching process. Our approach is thus distinguished in that it works with a variety of well-defined similarity notions and that it efficiently incorporates multiple types of knowledge. We describe a set of experiments on several real-world domains and show that GLUE proposes highly accurate semantic mappings. Finally, we extend GLUE to find complex mappings between ontologies and describe experiments that show the promise of the approach.

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Authors and Affiliations

  1. Department of Computer Science, University of Illinois at Urbana-Champaign, IL 61801, Urbana, USA

    AnHai Doan & Robin Dhamankar

  2. Department of Computer Science and Engineering, University of Washington, WA 98195, Seattle, USA

    Jayant Madhavan, Pedro Domingos & Alon Halevy

Authors
  1. AnHai Doan
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  2. Jayant Madhavan
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  3. Robin Dhamankar
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  4. Pedro Domingos
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  5. Alon Halevy
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Corresponding author

Correspondence to AnHai Doan.

Additional information

Received: 16 December 2002, Accepted: 16 April 2003, Published online: 17 September 2003

Edited by: Edited by B.V. Atluri, A. Joshi, and Y. Yesha

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Doan, A., Madhavan, J., Dhamankar, R. et al. Learning to match ontologies on the Semantic Web. VLDB 12, 303–319 (2003). https://doi.org/10.1007/s00778-003-0104-2

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