Ontology alignment using multiple contexts

Jeffrey Partyka, Neda Alipanah, Latifur Khan, Bhavani Thuraisingham, Shashi Shekhar

Research output: Contribution to journalConference articlepeer-review


Ontology alignment involves determining the semantic heterogeneity between two or more domain specifications by considering their associated concepts. Our approach considers name, structural and content matching techniques for aligning ontologies. After comparing the ontologies using concept names, we examine the instance data of the compared concepts and perform content matching using value types based on N-grams and Entropy Based Distribution (EBD). Although these approaches are generally sufficient, additional methods may be required. Subsequently, we compare the structural characteristics between concepts using Expectation-Maximization (EM). To illustrate our approach, we conducted experiments using authentic geographic information systems (GIS) data and generate results which clearly demonstrate the utility of the algorithms while emphasizing the contribution of structural matching.

Original languageEnglish (US)
JournalCEUR Workshop Proceedings
StatePublished - Dec 1 2008
Event7th International Semantic Web Conference, ISWC 2008 - Karlsruhe, Germany
Duration: Oct 28 2008Oct 28 2008


  • Dataset
  • Geographic Information Systems
  • Ontology
  • Ontology Alignment
  • Schema Matching


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