A process for generating quantitative belief functions

We present a structured methodology for transforming qualitative preference relationships among propositions into appropriate numeric representations. This approach will be useful in the difficult process of knowledge acquisition from experts on the degree of belief in various propositions or the probability of the truthfulness of those propositions. The approach implicitly (through the qualitative assignments) and explicitly (through the vague interval pairwise comparisons) provides for different levels of preference relationships. Among its advantages, it permits the expert to: explore the given problem situation, using linguistic quantifiers; avoid the premature use of numeric measures; and identify input data that are inconsistent with the theory of belief functions.