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Modeling Qualitative Assessments under the Belief Function Framework

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8764))

Abstract

This paper investigates the problem of preference modeling under the belief function framework. In this work, we introduce a new model that is able to generate quantitative information from qualitative assessments. Therefore, we suggest to represent the decision maker preferences in different levels where the indifference, strict preference, weak preference and incompleteness relations are considered. Introducing the weak preference relation separates the preference area from the indifference one by inserting an intermediate zone.

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References

  1. Ben Yaghlane, A., Denoeux, T., Mellouli, K.: Constructing belief functions from expert opinions. In: Proceedings of the 2nd International Conference on Information and Communication Technologies: from Theory to Applications (ICTTA 2006), Damascus, Syria, pp. 75–89 (2006)

    Google Scholar 

  2. Bryson, N., Mobolurin, A.: A process for generating quantitative belief functions. European Journal of Operational Research 115, 624–633 (1999)

    Article  MATH  Google Scholar 

  3. Ennaceur, A., Elouedi, Z., Lefevre, E.: Introducing incomparability in modeling qualitative belief functions. In: Torra, V., Narukawa, Y., López, B., Villaret, M. (eds.) MDAI 2012. LNCS, vol. 7647, pp. 382–393. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  4. Fodor, J., Roubens, M.: Fuzzy strict preference relations in decision making. In: Proceedings of the Second IEEE International Conference on Fuzzy Systems, pp. 1145–1149 (1993)

    Google Scholar 

  5. Pal, N., Bezdek, J., Hemasinha, R.: Uncertainty measures for evidential reasoning I: A review. International Journal of Approximate Reasoning 7, 165–183 (1992)

    Article  MathSciNet  MATH  Google Scholar 

  6. Pal, N., Bezdek, J., Hemasinha, R.: Uncertainty measures for evidential reasoning II: A review. International Journal of Approximate Reasoning 8, 1–16 (1993)

    Article  MathSciNet  MATH  Google Scholar 

  7. Perny, P., Roy, B.: The use of fuzzy outranking relations in preference modelling. Fuzzy Sets and Systems 49(1), 33–53 (1992)

    Article  MathSciNet  MATH  Google Scholar 

  8. Roubens, M., Vincke, P.: Preference modelling. Springer, Berlin (1985)

    Book  MATH  Google Scholar 

  9. Roy, B.: Pseudo-orders: Definition, properties and numerical representation. Mathematical Social Sciences 14, 263–274 (1987)

    Article  MathSciNet  MATH  Google Scholar 

  10. Shafer, G.: A Mathematical Theory of Evidence. Princeton University Press (1976)

    Google Scholar 

  11. Smets, P.: The application of the Transferable Belief Model to diagnostic problems. International Journal of Intelligent Systems 13, 127–158 (1998)

    Article  MATH  Google Scholar 

  12. Smets, P., Kennes, R.: The Transferable Belief Model. Artificial Intelligence 66, 191–234 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  13. Wong, S., Lingras, P.: Representation of qualitative user preference by quantitative belief functions. IEEE Transactions on Knowledge and Data Engineering 6, 72–78 (1994)

    Article  Google Scholar 

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© 2014 Springer International Publishing Switzerland

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Ennaceur, A., Elouedi, Z., Lefevre, É. (2014). Modeling Qualitative Assessments under the Belief Function Framework. In: Cuzzolin, F. (eds) Belief Functions: Theory and Applications. BELIEF 2014. Lecture Notes in Computer Science(), vol 8764. Springer, Cham. https://doi.org/10.1007/978-3-319-11191-9_19

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  • DOI: https://doi.org/10.1007/978-3-319-11191-9_19

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11190-2

  • Online ISBN: 978-3-319-11191-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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