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Identifying precedents under uncertainty

  • Legal Systyems
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Book cover Database and Expert Systems Applications (DEXA 1994)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 856))

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Abstract

Information about the case to be decided rarely is complete and precise. So dealing with imprecise information definitely is one of the major issues of legal decision making. In order to be able to identify a non-empty set of precedents most similar to our case, we introduce the Dempster-Shafer rule for combining information from independent sources and use the resulting mass functions to determine the importance of each precedent in our knowledge system. Additionally, the method is illustrated by an example.

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References

  1. A. de Korvin, R. Kleyle, R. Lea, The object recognition problem when features fail to be homogeneous, International Journal of Approximate Reasoning 1993; 8:141–162.

    Google Scholar 

  2. A. de Korvin, G. Quirchmayr, S. Hashemi, Legal decision making under uncertainty, in Proceedings of Expersys-93 (H.S. Nwana, T. Martelli, Eds.), i.i.t.t, 1993: 50–67.

    Google Scholar 

  3. R. Kleyle and A. de Korvin, Two methods for object identification with imprecise information. To be published in 1994.

    Google Scholar 

  4. R. Giles, Foundations for a theory of possibility, in Fuzzy Information and Decision Processes (M. M. Gupta and E. Sanchez, Eds.), North Holland Publishing Co., 193–195, 1982.

    Google Scholar 

  5. T. F. Gordon and G. Quirchmayr, Der Einsatz der Modellierungssprache OBLOG zum Entwurf von Juristischen Expertensystemen im Wege des Prototyping am Besipiel eines Modells des Verfahrens der Eidesstattlichen Versicherung, Springer IFB 143, 137–154, Berlin 1987.

    Google Scholar 

  6. J.-Y. Jaffray, Application of Linear utility theory to belief functions, in Uncertainty in Artificial Intelligence, Vol. 5, (Max Henrion, Ed.), New York, Elsevier Publishing Co., New York, 1–8, 1990.

    Google Scholar 

  7. S. B. Marsh and J. Soulsby, Outlines of English Law, McGraw-Hill, London, 124 ff., 1987.

    Google Scholar 

  8. R. Reiter, On Reasoning by Default, Proceedings of the 2nd Symposium on Theoretical Issues in Natural Language Processing, Urbana, Illinois.

    Google Scholar 

  9. P. Smetz, Belief functions versus probability functions, in Uncertainty in Artificial Intelligence, Vol. 5, (Max Henrion, Ed.), New York, Elsevier Publishing Co., New York, 1–8, 1990.

    Google Scholar 

  10. T. M. Strat, Decision analysis using belief functions, Intern. J. Approximate Reasoning 4, 391–417, 1990.

    Google Scholar 

  11. R. Susskind, Expert Systems in Law, Oxford University Press 1987.

    Google Scholar 

  12. A. Zebda, The Investigation of Cost Variances: A Fuzzy Set Theory Approach, Vol. 15, 1984, 359–388. Decision sciences.

    Google Scholar 

  13. R. Yager, A general approach to decision making with evidential knowledge. Uncertainty in Artificial Intelligence (L. N. Kanal and J. F. Lemmer, Eds.), North Holland, Amsterdam, 317–327, 1986.

    Google Scholar 

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Dimitris Karagiannis

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© 1994 Springer-Verlag Berlin Heidelberg

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de Korvin, A., Quirchmayr, G., Hashemi, S. (1994). Identifying precedents under uncertainty. In: Karagiannis, D. (eds) Database and Expert Systems Applications. DEXA 1994. Lecture Notes in Computer Science, vol 856. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-58435-8_196

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  • DOI: https://doi.org/10.1007/3-540-58435-8_196

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-58435-3

  • Online ISBN: 978-3-540-48796-8

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