Domain-Aware Ontology Matching

  • Kristian Slabbekoorn
  • Laura Hollink
  • Geert-Jan Houben
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7649)


The inherent heterogeneity of datasets on the Semantic Web has created a need to interlink them, and several tools have emerged that automate this task. In this paper we are interested in what happens if we enrich these matching tools with knowledge of the domain of the ontologies. We explore how to express the notion of a domain in terms usable for an ontology matching tool, and we examine various methods to decide what constitutes the domain of a given dataset. We show how we can use this in a matching tool, and study the effect of domain knowledge on the quality of the alignment.

We perform evaluations for two scenarios: artists and UMLS medical terms. To quantify the added value of domain knowledge, we compare our domain-aware matching approach to a standard approach based on a manually created reference alignment. The results indicate that the proposed domain-aware approach indeed outperforms the standard approach, with a large effect on ambiguous concepts but a much smaller effect on unambiguous concepts.


Domain Knowledge Pruning Strategy Link Open Data Positive Match Reference Alignment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Kristian Slabbekoorn
    • 1
  • Laura Hollink
    • 2
    • 3
  • Geert-Jan Houben
    • 2
  1. 1.Department of Computer ScienceTokyo Institute of TechnologyJapan
  2. 2.Web Information Systems GroupDelft University of TechnologyThe Netherlands
  3. 3.Knowledge Representation and Reasoning GroupVU AmsterdamThe Netherlands

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