This paper deals with enriched qualitative belief functions for reasoning under uncertainty and for combining information expressed in natural language through

Using qualitative methods to deal with imperfect information.

In this paper, we present a new 2-tuple linguistic representation model, i.e. Distribution Function Model (DFM), for combining imprecise qualitativeinformation

Martin and Osswald have recently proposed many generalizations of combination rules on quantitative beliefs in order to manage the conflict and to consider the

In this chapter, we propose in the DSmT framework, a new probabilistic transformation, called DSmP, in order to build a subjective probability measure from any