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Link to original content: https://doi.org/10.1007/978-3-642-10291-2_3
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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5883))

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Abstract

In the paper we show how rule-based inference can be made more flexible by exploiting semantic information associated with the concepts involved in the rules. We introduce flexible forms of common sense reasoning in which whenever no rule applies to a given situation, the inference engine can fire rules that apply to more general or to similar situations. This can be obtained by defining new forms of match between rules and the facts in the working memory and new forms of conflict resolution. We claim that in this way we can overcome some of the brittleness problems that are common in rule-based systems.

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References

  1. Borgida, A., Brachman, R.J., McGuinness, D.L., Alperin Resnick, L.: Classic: A Structural Data Model for Objects. In: Clifford, J., Lindsay, B.G., Maier, D. (eds.) SIGMOD Conference, pp. 58–67. ACM Press, New York (1989)

    Google Scholar 

  2. Borgida, A., Walsh, T., Hirsh, H.: Towards Measuring Similarity in Description Logics. In: Horrocks, I., Sattler, U., Wolter, F. (eds.) Description Logics. CEUR Workshop Proceedings, vol. 147, CEUR-WS.org (2005)

    Google Scholar 

  3. Broekstra, J., Kampman, A.: Serql: An RDF Query and Transformation Language. In: Proc. of International Semantic Web Conference (2004)

    Google Scholar 

  4. Buriano, L., Marchetti, M., Carmagnola, F., Cena, F., Gena, C., Torre, I.: The Role of Ontologies in Context-Aware Recommender Systems. In: MDM, p. 80. IEEE Computer Society, Los Alamitos (2006)

    Google Scholar 

  5. D’amato, C., Staab, S., Fanizzi, N.: On the influence of description logics ontologies on conceptual similarity. In: Gangemi, A., Euzenat, J. (eds.) EKAW 2008. LNCS (LNAI), vol. 5268, pp. 48–63. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  6. Eiter, T., Lukasiewicz, T., Schindlauer, R., Tompits, H.: Combining Answer Set Programming with Description Logics for the Semantic Web. In: Proc. KR 2004, pp. 141–151. AAAI Press, Menlo Park (2004)

    Google Scholar 

  7. Forgy, C.: Rete: A Fast Algorithm for the Many Patterns/Many Objects Match Problem. Artif. Intell. 19(1), 17–37 (1982)

    Article  Google Scholar 

  8. Levy, A.Y., Rousset, M.C.: Combining Horn Rules and Description Logics in Carin. Artif. Intell. 104(1-2), 165–209 (1998)

    Article  MATH  MathSciNet  Google Scholar 

  9. Rada, R., Mili, H., Bicknell, E., Blettner, M.: Development and Application of a Metric on Semantic Nets. IEEE Trans SMC 19, 17–30 (1989)

    Google Scholar 

  10. Resnik, P.: Using Information Content to Evaluate Semantic Similarity in a Taxonomy. In: XIth IJCAI, pp. 448–453 (1995)

    Google Scholar 

  11. Rosati, R.: Dl+log: Tight Integration of Description Logics and Disjunctive Datalog. In: Proc. KR 2006, pp. 68–78. AAAI Press, Menlo Park (2006)

    Google Scholar 

  12. Russell, S., Norvig, P.: Artificial Intelligence: a Modern Approach. Prentice-Hall, Englewood Cliffs (2002)

    Google Scholar 

  13. Stefik, M.: Introduction to Knowledge Systems. Morgan Kaufmann, San Francisco (1995)

    Google Scholar 

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Lombardi, I., Console, L. (2009). Common-Sense Rule Inference. In: Serra, R., Cucchiara, R. (eds) AI*IA 2009: Emergent Perspectives in Artificial Intelligence. AI*IA 2009. Lecture Notes in Computer Science(), vol 5883. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10291-2_3

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  • DOI: https://doi.org/10.1007/978-3-642-10291-2_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10290-5

  • Online ISBN: 978-3-642-10291-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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