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Building Corporate Knowledge Through Ontology Integration

  • Philip H. P. Nguyen
  • Dan Corbett
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4303)

Abstract

This paper presents an approach for building corporate knowledge, defined as the total knowledge acquired by an enterprise in its business dealings, through integration of its existing ontologies. We propose to represent corporate knowledge as the final merged ontology, defined under our formalism, in which a canon, or common ontology, is used as the standard under which all other ontologies are aligned. The canon is also enriched with knowledge gained during each ontology merging exercise. Our method ensures that all resulting ontologies are semantically consistent, compact and complete, as well as mathematically sound, so that formal reasoning could be conducted.

Keywords

Association Rule Knowledge Engineer Formal Concept Analysis Conceptual Graph Concept Type 
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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References

  1. 1.
    Chein, M., Mugnier, M.L.: Concept Types and Coreference in Simple Conceptual Graphs. In: 12th International Conference on Conceptual Structures, Huntsville, Alabama, USA (2004)Google Scholar
  2. 2.
    Corbett, D.: Reasoning and Unification over Conceptual Graphs. Kluwer Academic Publishers, New York (2003)MATHGoogle Scholar
  3. 3.
    Corbett, D.: Filtering and Merging Knowledge Bases: a Formal Approach to Tailoring Ontologies. In: Paris, C., Colineau, N. (eds.) Revue d’Intelligence Artificielle, Special Issue on Tailored Information Delivery, September/October 2004, pp. 463–481 (2004)Google Scholar
  4. 4.
    Ganter, B., Wille, R.: Formal Concept Analysis: Mathematical Foundations. Springer, Heidelberg (1996-German version) (1999-English translation)Google Scholar
  5. 5.
    Nguyen, P., Corbett, D.: A Basic Mathematical Framework for Conceptual Graphs. IEEE Transactions on Knowledge and Data Engineering 18(2), 261–271 (2006)CrossRefGoogle Scholar
  6. 6.
    Nguyen, P.: MultiOntoMergePrototype, http://users.on.net/~pnguyen/cgi/multiontomerge.pl
  7. 7.
    Nicolas, S., Moulin, B., Mineau, G.: sesei: a CG-Based Filter for Internet Search Engines. In: 11th International Conference on Conceptual Structures, Dresden, Germany (2003)Google Scholar
  8. 8.
    Sowa, J.: Knowledge Representation: Logical, Philosophical, and Computational Foundations. Brooks Cole Publishing Co., Pacific Grove (1999)Google Scholar
  9. 9.
    Stumme, G., Maedche, A.: FCA-Merge: Bottom-Up Merging of Ontologies. In: 7th International Conference on Artificial Intelligence, Seattle, USA (2001)Google Scholar
  10. 10.
    Wille, R.: Restructuring Lattice Theory: an Approach based on Hierarchies of Concepts. In: Rival, I. (ed.) Ordered Sets, Reidel, Dordrecht-Boston (1982)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Philip H. P. Nguyen
    • 1
  • Dan Corbett
    • 2
  1. 1.Department of Justice, Government of South AustraliaJustice Technology ServicesAdelaideAustralia
  2. 2.Science Applications International CorporationMcLeanUSA

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