 None of the above methods could take into account the popularity of a specific information item. This meant that those operators could not capture the view of the majority. The first to introduce a majority postulate for the merging of several knowledge bases were Lin and Mendelzon (1999). The idea was inspired by the majority rule in social choice theory. However, their majority postulate includes a notion of partial support that captures the specificity of knowledge merging with respect to voting, and is not limited to count the number of bases supporting a proposition a vs. the number of bases containing \(\neg a\). A knowledge base was defined to partially support a literal l if there is a proposition a that contains no atoms appearing in l, such that the agent believes either l or a is true without knowing which one. A model-theoretic characterization of the postulates and specific merging operators are given in Lin and Mendelzon (1999). In the belief merging literature, sources of information are generally assumed to be equally reliable. One way to help to solve the conflict is to relax this assumption as, for example, in the extension to merging weighted knowledge bases given in (Lin 1996) or in prioritized knowledge bases (Benferhat et al. 1998; Cholvy 1998; Delgrande et al. 2006).