Nevertheless, there exist two general approaches to this general scheme, depending on the problem to be dealt, with. The first one corresponds to the aggregation of preferences given by several individuals of a group or the aggregation of criteria to satisfy in order to make a decision. In both cases, a consensus is looked for, which means that a solution of the problem must satisfy as much as possible individual or criteria. The second approach concerns the fusion of evidence provided by several sources. In this framework, complementary information is used to construct a global description of the object from partial views and to eliminate inconsistencies from the elementary descriptions.
Several methodologies are useful to manage such imperfect information.
Among the most important ones are probability theory , evidence theory , fuzzy set theory and possibility theory . I will focus my work on the last ones. Fusion is a fundamental phase of data mining , which purpose is the exploration of data bases in order to find information no directly apprehensible. For example forms, rules, classifications, regularities, dependencies. Data mining is a key field for all organizations subjected to a information stream, from which they want to extract the essential that interest them.