Interpreting Belief Functions as Dirichlet Distributions

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Interpreting Belief Functions as Dirichlet Distributions
Traditional Dempster Shafer belief theory does not provide a simple method for judging the effect of statistical and probabilistic data on belief functions and vice versa. This puts belief theory in isolation from probability theory and hinders fertile cross-disciplinary developments, both from a theoretic and an application point of view. It can be shown that a bijective mapping exists between Dirichlet distributions and Dempster-Shafer belief functions, and the purpose of this paper is to describe this correspondence. This has three main advantages; belief based reasoning can be applied to statistical data, statistical and probabilistic analysis can be applied to belief functions, and it provides a basis for interpreting and visualizing beliefs for the purpose of enhancing human cognition and the usability of belief based reasoning systems.
Audun Jøsang, Zied Elouedi
Added 07 Jun 2010
Updated 07 Jun 2010
Type Conference
Year 2007
Authors Audun Jøsang, Zied Elouedi
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