Most of modern systems for information retrieval, fusion and management have to deal with more and more qualitative information (by linguistic labels) besides information expressed quantita- tively (by numbers), since human reports are better and easier expressed in natural language than with numbers. In this paper, Herrera-Martínez’s 2-Tuple linguistic representation model is extended for reasoning with uncertain and qualitative information in Dezert-Smarandache Theory (DSmT) framework, in order to overcome the limitations of current approaches, i.e., the lack of precision in the final results of linguistic information fusion according to 1-Tuple representation ( q 1). The linguistic information which expresses the expert’s qualitative beliefs is expressed by means of mixed 2 Tuples (equidistant linguistic labels with a numeric biased value). Together with the 2-Tuple representation model, some basic operators are presented to carry out the fusion operation among qualitative in- formation sources. At last, through simple example how 2-Tuple qualitative DSmT-based ( q 2DSmT) fusion rules can be used for qualitative reasoning and fusion under uncertainty, which advantage is also showed by comparing with other methods.
展开▼
