Skip to main content

Formal Method for Aligning Goal Ontologies

  • Chapter
  • 496 Accesses

Part of the book series: Studies in Computational Intelligence ((SCI,volume 109))

Summary

Many distributed heterogeneous systems interoperate and exchange information between them. Currently, most systems are described in terms of ontologies. When ontologies are distributed, the problem of finding related concepts between them arises. This problem is undertaken by a process which defines rules to relate relevant parts of different ontologies, called “Ontology Alignment.” In literature, most of the methodologies proposed to reach the ontology alignment are semi automatic or directly conducted by hand. In the present paper, we propose an automatic and dynamic technique for aligning ontologies. Our main interest is focused on ontologies describing services provided by systems. In fact, the notion of service is a key one in the description and in the functioning of distributed systems. Based on a teleological assumption, services are related to goals through the paradigm ‘Service as goal achievement’, through the use of ontologies of services, or precisely goals. These ontologies are called “Goal Ontologies.” So, in this study we investigate an approach where the alignment of ontologies provides full semantic integration between distributed goal ontologies in the engineering domain, based on the Barwise and Seligman Information Flow (noted IF) model.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bailin S, Truszkowski W (2001) Ontology Negotiation between Agents Supporting Intelligent Information Management. In: Workshop on Ontologies in Agent Systems

    Google Scholar 

  2. Chittaro L, Guida G, Tasso G, Toppano E (1993) Functional and teleological knowledge in the multi modeling approach for reasoning about physical systems: A case study in diagnosis. IEEE Transactions on Systems, Man, and Cybernetics, 23(6): 1718–1751

    Article  Google Scholar 

  3. Dapoigny R, Benoit E, Foulloy L (2003) Functional Ontology for Intelligent Instruments. In: Foundations of Intelligent Systems. LNAI2871, pp 88–92

    Google Scholar 

  4. Dapoigny R, Barlatier P, Mellal N, Benoit E, Foulloy L (2005) Inferential Knowledge Sharing with Goal Hierarchies in Distributed Engineering Systems. In: IIAI05, Pune (India), pp 590–608

    Google Scholar 

  5. Dapoigny R, Mellal N, Benoit E, Foulloy L (2004) Service Integration in Distributed Control Systems: an approach based on fusion of mereologies. In: IEEE Conf. on Cybernetics and Intelligent Systems (CIS’04), Singapour, December 2004, pp 1282–1287

    Google Scholar 

  6. Dapoigny R, Barlatier P, Benoit E, Foulloy L (2005) Formal Goal generation for Intelligent Control systems. In: 18th International Conference on Industrial & Engineering Applications of Artificial Intelligence & Expert Systems LNAI 3533, Springer, pp 712–721

    Google Scholar 

  7. Dardenne A, Lamsweerde A, Fickas S (1993) Goal-directed requirements acquisition. Science of Computer Programming, 20: 3–50

    Article  MATH  Google Scholar 

  8. Dooley K, Skilton P, Anderson J (1998) Process knowledge bases: Facilitating reasoning through cause and effect thinking. Human Systems Management, 17(4): 281–298

    Google Scholar 

  9. Fikes R (1996) Ontologies: What are they, and where’s the research? Principles of Knowledge Representation and Reasoning, 652–654

    Google Scholar 

  10. Gorton I, Haack J, McGee D, Cowell J, Kuchar O, Thomson J (2003) Evaluating Agent Architectures: Cougaar, Aglets and AAA. In: SELMAS, pp 264–278

    Google Scholar 

  11. Gruber T (1993) A translation approach to portable ontology specifications. Knowledge Acquisition, 5(2): 199–220

    Article  Google Scholar 

  12. Hertzberg J, Thiebaux S (1994) Turning an action formalism into a alanner: A case study. Journal of Logic and Computation, 4: 617–654

    Article  MATH  Google Scholar 

  13. Huber M (1999) A BDI-Theoretic Mobile Agent Architecture. In AGENTS 99 Proceedinf. of the Third Annual Conference on Autonomous Agents (1999) Seattle, WA, USA ACM, pp 236–243

    Google Scholar 

  14. Kalfoglou Y, Schorlemmer M (2002) Information Flow based ontology mapping. In: Proceedings 1st International Conference on Ontologies, Databases and Applications of Semantics(ODBASE’02), Irvine, CA, USA

    Google Scholar 

  15. Kalfoglou Y, Schorlemmer M (2003) Ontology mapping: the state of the art. The Knowledge Engineering Review, 18:1–31

    Article  Google Scholar 

  16. Kalfoglou Y, Schorlemmer M (2003) IF-Map: An ontology mapping method based on information flow theory. Journal of Data Semantics, S. Spaccapietra et al. (eds.), vol. 11, Springer, Berlin Heidelberg New York

    Google Scholar 

  17. Kalfoglou Y, Schorlemmer M (2004) Formal Support for Representing and Automating Semantic Interoperability. In: Proceedings of the 1st European Semantic Web Symposium (ESWS’04), Heraklion, Crete

    Google Scholar 

  18. Kalfoglou Y, Hu B, Reynolds D (2005) On Interoperability of Ontologies for Web-based Educational Systems. In: WWW 2005 workshop on Web-based educational systems, Chiba city, Japan

    Google Scholar 

  19. Kent RE (2000) The information flow foundation for conceptual knowledge. In: Dynamism and Stability in Knowledge Organization. Proceedings of the Sixth International ISKO Conference. Advances in Knowledge Organization, 7: 111–117

    Google Scholar 

  20. Kitamura Y, Mizoguchi R (1998) Functional Ontology for Functional Understanding. In: 12th International Workshop on Qualitative Reasoning AAAI Press, pp 77–87

    Google Scholar 

  21. Lifschitz V (1993) A Theory of Actions. In: 9th International Joint Conference on Artificial Intelligence, M. Kaufmann (ed.), pp 432–437

    Google Scholar 

  22. Lind M (1994) Modeling goals and functions of complex industrial plant. Journal of Applied Artificial Intelligence, 259–283

    Google Scholar 

  23. Mellal N, Dapoigny R, Foulloy L (2006) The Fusion Process of Goal Ontologies using Intelligent Agents in Distributed Systems. In: International IEEE Conference on Intelligent Systems, London, UK, September, pp. 42–47

    Google Scholar 

  24. Myers K (1996) A Procedural Knowledge Approach to Task-Level Control. In: Proceedings of the Third International Conference on Artificial Intelligence Planning Systems, pp 158–165

    Google Scholar 

  25. Rao AS, Georgeff MP (1995) BDI Agents: From Theory to Practice. In: First International Conference on Multi-Agent Systems (ICMAS-95), SanFranciso, USA, pp 312–319

    Google Scholar 

  26. Russel S, Norvig P (1995) Artificial Intelligence, A Modern Approach, Prentice Hall, Englewood Cliffs, NJ

    Google Scholar 

  27. Schorlemmer M, Kalfoglou Y (2003) Using Information-Flow Theory to enable Semantic Interoperability, Technical report EDI-INF-RR-0161 University of Edinburgh

    Google Scholar 

  28. Varzi A (2000) Mereological commitments. Dialectica, 54: 283–305

    Article  Google Scholar 

  29. Zambonelli F, Jennings NR, Wooldridge M (2003) Developing MultiAgent systems: The Gaia methodology. Journal of ACM Transactions on Software Engineering and Methodology, 12(3): 317–370

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Mellal, N., Dapoigny, R., Foulloy, L. (2008). Formal Method for Aligning Goal Ontologies. In: Chountas, P., Petrounias, I., Kacprzyk, J. (eds) Intelligent Techniques and Tools for Novel System Architectures. Studies in Computational Intelligence, vol 109. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77623-9_16

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-77623-9_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-77621-5

  • Online ISBN: 978-3-540-77623-9

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics