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Ranking from Pairwise Comparisons in the Belief Functions Framework

  • Marie-Hélène Masson
  • Thierry Denœux
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 164)

Abstract

The problem of deriving a binary relation over alternatives based on paired comparisons is studied. The problem is tackled in the framework of belief functions, which is well-suited to model and manipulate partial and uncertain information. Starting from the work of Tritchler and Lockwood [8], the paper proposes a general model of mass allocation and combination, and shows how to practically derive a complete or a partial ranking of the alternatives. A small example is provided as an illustration.

Keywords

Partial Order Linear Order Paired Comparison Mass Function Linear Extension 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Heudiasyc, UMR CNRS 6599UPJVCompiègneFrance
  2. 2.Heudiasyc, UMR CNRS 6599UTCCompiègneFrance

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