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Automatic Ontology Evolution in Open and Dynamic Computing Environments

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Computational Collective Intelligence. Technologies and Applications (ICCCI 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6423))

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Abstract

Automated computing in open and dynamic computing environments requires automatic update and revision of the Knowledge Bases (KBs) to keep the KBs up to date with the dynamics in the environment and correct incorrect knowledge held in the KBs respectively. Furthermore, the truthfulness, applicability and validity of this knowledge depend on the context under which the knowledge is to be used. This then calls for the development of solutions to enable KBs to (i) be evolved over time enabling them to keep up to date with the evolving world or changes in the world’s conceptualisation, (ii) allow situational reasoning, and (iii) reasoning under uncertain, incomplete and inconsistent knowledge. The emerging fielding of probabilistic ontologies is impregnated with promises to resolve such issues. However, an investigation on how such knowledge representations can be objectively and rationally evolved is needed. This paper presents issues, methods and ideas towards rational probabilistic ontology evolution in open and dynamic computing environments.

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References

  1. Flouris, G.: On Belief Change and Ontology Evolution. PhD thesis, University of Crete, Greece (2006) (unpublished)

    Google Scholar 

  2. Flouris, G., Plexousakis, D., Antoniou, G.: Evolving Ontology Evolution. In: Wiedermann, J., Tel, G., Pokorný, J., Bieliková, M., Štuller, J. (eds.) SOFSEM 2006. LNCS, vol. 3831, pp. 14–29. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  3. Bundy, A., Chan, M.: Towards ontology evolution in physics. In: Hodges, W., de Queiroz, R. (eds.) Logic, Language, Information and Computation. LNCS (LNAI), vol. 5110, pp. 98–110. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  4. Yang, Y., Calmet, J.: OntoBayes: An Ontology-Driven Uncertainty Model. In: CIMCA/IAWTIC 2005, pp. 45–463 (2005)

    Google Scholar 

  5. Haase, P., Völker, J.: Ontology Learning and Reasoning - Dealing with Uncertainty and Inconsistency. In: ISWC-URSW 2005, pp. 45–55 (2005)

    Google Scholar 

  6. Scharrenbach, T., Bernstein, A.: On the Evolution of Ontologies using Probabilistic Description Logics. In: Proceedings of the First ESWC Workshop on Inductive Reasoning and Machine Learning on the Semantic Web (2009)

    Google Scholar 

  7. Ding, Z., Peng, Y.: A probabilistic extension to ontology language owl. In: Proceedings of the International Conference on System Sciences (HICSS 2004), vol. 4, pp. 1–15. IEEE Computer Society, Washington (2004)

    Google Scholar 

  8. Cannataro, M., Talia, D.: Semantic and Knowledge Grids: Building the Next -Generation Grid. IEEE Intelligent Systems - Special Issue on e-Science 19(1), 56–63 (2004)

    Article  Google Scholar 

  9. De Roure, D., Jennings, N.R., Shadbolt, N.: The Semantic Grid: A Future e-Science Infrastructure. In: Berman, F., Hey, A.J.G., Fox, G. (eds.) Grid Computing: Making the Global Infrastructure a Reality, pp. 437–470. John Wiley & Sons, Chichester (2003)

    Chapter  Google Scholar 

  10. Brezany, P., Goscinski, A., Janciak, I., Tjoa, A.M.: The development of a Wisdom Autonomic Grid. In: Proceedings of the Workshop on Knowledge Grid and Grid Intelligence 2004, China (2004)

    Google Scholar 

  11. Zhuge, H.: Semantics, Resource and Grid. Future Generation Computer Systems 20(1), 1–5 (2004)

    Article  Google Scholar 

  12. Liu, P., Nie, G., Chen, D., Fu, Z.: The knowledge grid based intelligent electronic commerce recommender systems. In: Proceedings of the IEEE International Conference on Service-Oriented Computing and Applications, Newport Beach, pp. 223–232 (2007)

    Google Scholar 

  13. Laskey, K.B.: MEBN.: A Logic for Open-World Probabilistic Reasoning. The Volnegau School of Information Technology and Engineering. George Mason University, Fairfax, VA, USA (2005)

    Google Scholar 

  14. Ngo, L., Haddawy, P.: Answering queries from context-sensitive probabilistic knowledge bases. Theoretical Computer Science 171(1-2), 147–177 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  15. Costa, P.C.G.D., Laskey, K.B., Laskey, K.J., Pool, M.: Uncertainty Reasoning for the Semantic Web. In: Proceedings of the International Semantic Web Conference, ISWC 2005, Workshop 3, ISWC-URSW, Galway, Ireland (2005)

    Google Scholar 

  16. Lukasiewicz, T.: Probabilistic Default Reasoning with Conditional Constraints. Ann. Math. Artif. Intell. 34(1-3), 35–88 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  17. Domingos, P., Kok, S., Lowd, D., Poon, H., Richardson, M., Singla, P.: Markov Logic. In: De Raedt, L., Frasconi, P., Kersting, K., Muggleton, S.H. (eds.) Probabilistic Inductive Logic Programming. LNCS (LNAI), vol. 4911, pp. 92–117. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  18. Costa, P.C.G.D.: Bayesian Semantics for the Semantic Web. Doctoral Dissertation. Department of Systems Engineering and Operations Research, George Mason University, Fairfax, VA, USA (2005)

    Google Scholar 

  19. Yang, Y., Calmet, J.: OntoBayes: An Ontology-Driven Uncertainty Model. In: CIMCA/IAWTIC 2005, pp. 457–463 (2005)

    Google Scholar 

  20. Alchourron, C., Gärdenfors, P., Makinson, D.: On the Logic of Theory Change: Partial Meet Contraction and Revision Functions. Journal of Symbolic Logic 50, 510–530 (1985)

    Article  MathSciNet  MATH  Google Scholar 

  21. Katsuno, H., Mendelzon, A.O.: On the Difference between Updating a Knowledge Base and Revising It. In: KR 1991, pp. 387–394 (1991)

    Google Scholar 

  22. Koller, D., Pfeffer, A.: Object-oriented Bayesian networks. In: Geiger, D., Shenoy, P.P. (eds.) Proceedings of the 13th Conference on Uncertainty in Artificial Intelligence, pp. 302–313. Morgan Kaufmann, San Francisco (1997)

    Google Scholar 

  23. Friedman, N., Getoor, L., Koller, D., Pfeffer, A.: Learning Probabilistic Relational Models. In: IJCAI 1999, pp. 1300–1309 (1999)

    Google Scholar 

  24. Boutilier, C.: A Unified Model of Qualitative Belief Change: A Dynamical Systems Perspective. Artif. Intell. 98(1-2), 281–316 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  25. Mazzieri, M., Dragoni, A.F.: Ontology Revision as Non-Prioritized Belief Revision. In: ESOE 2007, pp. 58–69 (2007)

    Google Scholar 

  26. Flouris, G., Plexousakis, D.: Bridging Ontology Evolution and Belief Change. In: Antoniou, G., Potamias, G., Spyropoulos, C., Plexousakis, D. (eds.) SETN 2006. LNCS (LNAI), vol. 3955, pp. 486–489. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  27. Friedman, N., Halpern, J.Y.: Modeling belief in dynamic systems part II: revision and update. Journal of Artificial Intelligence Research 10(1), 117–167 (1999)

    MathSciNet  MATH  Google Scholar 

  28. Guelfi, N., Pruski, C., Reynaud, C.: Understanding Supporting Ontology Evolution by Observing the WWW Conference. In: ESOE 2007, pp. 19–32 (2007)

    Google Scholar 

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Authors and Affiliations

  1. Centre for Mobile e-Service for Development, University of Zululand, RSA

    Edgar Jembere, Sibusiso S. Xulu & Matthew O. Adigun

Authors
  1. Edgar Jembere
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  2. Sibusiso S. Xulu
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  3. Matthew O. Adigun
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Editor information

Editors and Affiliations

  1. Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, 415 Chien-Kung Road, 807, Kaohsiung, Taiwan

    Jeng-Shyang Pan

  2. Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, #43, Sec.4, Keelung Rd., 106, Taipei, Taiwan

    Shyi-Ming Chen

  3. Institute of Informatics, Wroclaw University of Technology, Str. Wyb. Wyspianskiego 27, 50-370, Wroclaw, Poland

    Ngoc Thanh Nguyen

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Jembere, E., Xulu, S.S., Adigun, M.O. (2010). Automatic Ontology Evolution in Open and Dynamic Computing Environments. In: Pan, JS., Chen, SM., Nguyen, N.T. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2010. Lecture Notes in Computer Science(), vol 6423. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16696-9_14

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  • DOI: https://doi.org/10.1007/978-3-642-16696-9_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16695-2

  • Online ISBN: 978-3-642-16696-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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