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Expanding Knowledge Source with Ontology Alignment for Augmented Cognition

  • Jeong-Woo Son
  • Seongtaek Kim
  • Seong-Bae Park
  • Yunseok Noh
  • Jun-Ho Go
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7063)

Abstract

Augmented cognition on sensory data requires knowledge sources to expand the abilities of human senses. Ontologies are one of the most suitable knowledge sources, since they are designed to represent human knowledge and a number of ontologies on diverse domains can cover various objects in human life. To adopt ontologies as knowledge sources for augmented cognition, various ontologies for a single domain should be merged to prevent noisy and redundant information. This paper proposes a novel composite kernel to merge heterogeneous ontologies. The proposed kernel consists of lexical and graph kernels specialized to reflect structural and lexical information of ontology entities. In experiments, the composite kernel handles both structural and lexical information on ontologies more efficiently than other kernels designed to deal with general graph structures. The experimental results also show that the proposed kernel achieves the comparable performance with top-five systems in OAEI 2010.

Keywords

Knowledge Source Property Graph Concept Graph Lexical Information Levenshtein Distance 
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 2011

Authors and Affiliations

  • Jeong-Woo Son
    • 1
  • Seongtaek Kim
    • 1
  • Seong-Bae Park
    • 1
  • Yunseok Noh
    • 1
  • Jun-Ho Go
    • 1
  1. 1.School of Computer Science and EngineeringKyungpook National UniversityKorea

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